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Top instrument firms in 2017

C&en’s ranking of scientific equipment makers reflects strong sales to a broad range of customers, by marc s. reisch, february 26, 2018 | a version of this story appeared in volume 96, issue 9.

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Last year was a good one for makers of life sciences and analytical instruments thanks to positive macroeconomic conditions, including low energy prices, a surging U.S. economy, and recovery in Europe. Overall instrument sales in 2017 for the 20 firms that C&EN tracks rose 9.5%.

Given the pace of industry consolidation during the past few years, it’s no surprise that the top five firms accounted for 54% of sales, versus 52% in 2016 . Thermo Fisher Scientific, among the most aggressive industry consolidators, alone accounted for 22% of the Top 20’s instrument sales.

The top five companies account for 54% of the sales of the top 20.

The top 10 companies account for 79% of the sales of the top 20.

Of the top 20 firms, eight are U.S. based, seven are from Europe, and five are based in Japan.

The top 10 firms on the list were responsible for 79% of sales, up from 77% in 2016. Combined sales growth for the top 10 was up 11.5% from last year.

This year’s list reflects several changes. Water analysis expert Xylem Analytics is no longer in the ranking because parent Xylem combined its analytics division with large software and analytics acquisitions, making it impossible to break out the instrument component.

Other changes include swaps in position. Roche Diagnostics, for example, switched with Agilent Technologies to become numbers four and five, respectively, in the ranking. Mettler-Toledo International and Bruker did a similar switch to positions seven and eight.

The most notable change in position was for Nikon, which fell four places after the firm separated its microscope business into two units, allowing C&EN to separate research instrument sales from industrial equipment sales.

On average, only about 25% of overall sales for the ranked companies are of analytical and life sciences lab instruments. Many also sell industrial measuring devices and other non-research-related equipment. C&EN excludes those businesses whenever possible.

The lion’s share of most of the surveyed company’s sales come from consumables, software, and services. When companies improve detail in their financial reports, C&EN can improve the clarity of its rankings, as was the case for Nikon. We restated Bruker’s figures for similar reasons.

In addition to the ranking, C&EN provides short profiles of the top 20 companies. The profiles review key changes that affected the industry leaders during 2017 and offer a peek into where they may be headed this year.

Related: Thermo Fisher to acquire FEI

1 Thermo Fisher Scientific

▸ 2017 instrument sales: $5.65 billion

The purchase of scanning electron microscope maker FEI and genetic analysis firm Affymetrix in 2016 significantly boosted Thermo Fisher Scientific’s instrument sales in 2017 to 27% of total sales, from 24% in 2016. But in 2017, its acquisitions were outside the instrumentation space. The firm bought process systems maker Finesse Solutions early in the year and then followed with the purchase of cloud computing firm Core Informatics to beef up its scientific data management capabilities. The acquisitive instrument maker’s biggest move last year was the $7.2 billion purchase of Patheon , a contract drugmaker. The move puts Thermo Fisher into pharmaceutical services in a big way and heralds a move outside its traditional hardware and consumables space. CEO Marc Casper said the purchase “significantly enhanced our value proposition ... for pharma and biotech customers.” However, Thermo Fisher apparently does not intend to cut back on its instrumentation orientation. Late last year it acquired Phenom-World, a Dutch maker of desktop scanning electron microscopes. In addition to being the instrument sales leader, Thermo Fisher is the leader in R&D spending, having invested $888 million last year in the development of instruments, assays, and other products.

Related: Thermo Fisher wins contest for Affymetrix

▸  2017 instrument sales: $2.28 billion

Danaher transformed itself in 2016 with the spin-off of its $6 billion industrial technologies business as Fortive. The conglomerate’s focus is now on its life sciences, diagnostics, dental, environmental, and applied businesses. Reviewing the firm’s fourth-quarter results, CEO Tom Joyce reported strong performance in the Beckman Coulter Life Sciences flow cytometry and particle counting business. The Leica Microsystems microscope business saw good growth in medical and research markets in Western Europe and China. And for mass spectrometry subsidiary Sciex, Danaher reported strength in the food, environmental, and pharmaceutical markets. In October 2017, Danaher completed the purchase of IDBS, a U.K.-based life sciences informatics firm. Joyce said IDBS will help users of its instruments make better and faster scientific decisions.

▸  2017 instrument sales: $2.04 billion

Shimadzu’s instrument sales rose more than 5% in 2017. The Japanese firm attributed the growth to the strong economy in China, the ongoing recovery in North America, and a moderate recovery in the European Union. In its analytical and measuring instruments unit, Shimadzu reported strong mass spectrometer sales to North American government and chemical industry customers. Sales of liquid chromatography equipment to the drug industry were healthy. Sales in China were strong across the board for mass spectrometers, liquid chromatographs, gas chromatographs, and environmental measurement equipment. The firm says it plans to invest in advanced health care and to employ artificial intelligence and internet of things technologies to be more competitive.

4 Roche Diagnostics

▸  2017 instrument sales: $1.95 billion

Sales of molecular diagnostic instruments and tests by the Swiss drug and diagnostics firm grew more than 4% in 2017. Most of the growth came from the gene sequencing area. In November, the diagnostic business bulked up its analytics capability with Roche’s purchase of U.S.-based Viewics. Roche says Viewics’s software will enable labs to make faster data-driven decisions. In January, Roche formed a pact with GE Healthcare to develop digital clinical records management and support. The pair will initially focus on improving management of personalized treatments for people with cancer or in need of critical care.

Related: Agilent acquires Raman spectroscopy firm

5 Agilent Technologies

▸  2017 instrument sales: $1.94 billion

In 2017, Agilent Technologies’ sales increased about 6% to nearly $4.5 billion. About $1.9 billion, or 43% of sales, came from instruments, and sales of instruments alone rose almost 3% for the year. Demand from China was strong, CEO Mike McMullen told investors during the firm’s fourth-quarter conference call. Demand from pharmaceutical customers was also strong, and demand from Europe and the chemical and energy markets exceeded expectations, he said. In July, Agilent expanded its instrumentation arsenal with the acquisition of Cobalt Light Systems for $52 million. The England-based firm took Agilent into the Raman spectroscopy market with a line of benchtop and portable instruments that allow users to identify materials without opening containers.

With few exceptions, instrument makers increased sales in 2017.

Note: Results are for the calendar year unless otherwise stated. Some figures were converted at relevant average exchange rates for 2017. a Company estimates for fiscal year ending March 31, 2018. b Results for instrumentation sales in this division alone. c Fiscal year ended Oct. 31, 2017. d Fiscal year ended Sept. 30, 2017. e Estimate based on company outlook. f Reporting segments changed for fiscal year ending March 31, 2018. Sources: C&EN, company data

6 Zeiss Group

▸  2017 instrument sales: $1.74 billion

Germany’s Zeiss Group boasted more than $6 billion in overall 2017 sales of equipment used in the medical, semiconductor, and vision care sectors. C&EN reports the sales in Zeiss’s Research & Quality Technology segment, which manufactures microscopes as well as industrial measurement systems. The firm said the microscopy business was stable during the year, mostly because of demand from industrial customers. The industrial measurement side of the business benefited from developments in the automotive market. The firm also acknowledged growing competitive pressure.

7 Mettler-Toledo International

▸  2017 instrument sales: $1.36 billion

Laboratory instruments accounted for about half of Mettler-Toledo’s total revenues in 2017. The firm sells a mix of instruments, including balances, pipettes, titrators, and physical and thermal analyzers used for sample preparation, benchtop work, and materials characterization. The firm also offers lab software, process analytical instruments, and automated chemical synthesis systems. Mettler-Toledo hesitated to forecast future demand in its most recent financial report, noting that “economic uncertainty remains in certain regions of the world.”

▸  2017 instrument sales: $1.33 billion

Bruker had a decent 2017. Overall revenues increased almost 10% to about $1.8 billion. The firm serves a variety of customers in areas such as the life sciences, drug discovery, chemicals, metals, and material sciences. Its instruments include mass spectrometers, nuclear magnetic resonance spectrometers, fluorescence microscopes, and molecular diagnostic tools. Bruker CEO Frank Laukien reported to investors that the firm’s core scientific instrument business had “low-single-digit year-over-year organic revenue growth.” He expects a better 2018. The situation is reversed for the firm’s superconducting-wire segment, which had mid-teen revenue growth in 2017 but is expected to have low-single-digit growth in 2018. Consumables, software, and accessories accounted for 25% of 2017 revenues, according to the firm.

9 Waters Corp.

▸   2017 instrument sales: $1.18 billion

Sales were up 7% overall for Waters Corp. in 2017, marking a solid year for the chromatography and mass spectrometry expert. Sales of instruments, which make up a little more than half of the firm’s revenue, rose nearly 6%. Service and consumables sales increased 7% and 8%, respectively. Sales growth for pharmaceutical customers slipped from 10% in 2016 to 7% in 2017, CEO Chris O’Connell told investors during Waters’s fourth-quarter conference call. The firm’s strategy, he added, is to “emphasize the vast opportunities in our pharmaceutical business.” During the year, Waters, which often goes it alone, signed a comarketing agreement with Wyatt Technology that couples Wyatt’s multiangle light-scattering detector with Waters’s ultra-high-performance liquid chromatography system.

10 Eppendorf

▸  2017 instrument sales: $773 million

A private German company, Eppendorf develops and sells instruments, consumables, and services for handling liquids, cells, and samples in the lab. Because Eppendorf does not break out its instrumentation sales, its place in C&EN’s ranking is based on total sales. And even those sales are an estimate, based on projections from mid-2017. In April, CEO Thomas Bachmann estimated that Eppendorf’s sales would grow 5% in 2017, or “slightly above the industry average.” The firm also reported good progress in connecting with customers’ electronic procurement systems. By doing so with major customers, especially in the U.S., the firm said it nearly doubled sales through those systems.

11 Bio-Rad Laboratories

▸  2017 instrument sales: $764 million

Bio-Rad Laboratories provides a range of life sciences research and clinical diagnostic products. The company did not report full-year results before this ranking was published, so C&EN derived its figures from estimates in the firm’s third-quarter report. In February 2017, Bio-Rad completed the $87 million acquisition of RainDance Technologies, which develops methods to study biological reactions in droplets. Bio-Rad says the purchase will extend its offerings in next-generation sequencing and DNA amplification.

12 PerkinElmer

▸  2017 instrument sales: $700 million

Overall sales at PerkinElmer rose nearly 7% in 2017, but instrument sales slipped 6%. The firm, whose instruments can be used in environmental, food, and metal analysis, has been emphasizing diagnostics and drug discovery. Early in the year, it completed the sale of its medical imaging business to Varex Imaging. Soon after, it announced the acquisition of Euroimmun Medical Laboratory Diagnostics for $1.3 billion. The deal brought PerkinElmer a $310 million-per-year business that uses immunohistochemical and biochemical methods to diagnose disease. In January, the firm bought Tulip Diagnostics, an Indian maker of reagents, kits, and instruments for malaria, HIV, and hepatitis diagnosis. Looking to 2018, PerkinElmer CEO Rob Friel told investors that he sees a favorable macroeconomic environment. Sales growth in China could be in the low double digits, he said.

▸  2017 instrument sales: $645 million

In addition to scientific and metrology instruments, JEOL sells semiconductor, industrial, and medical equipment. The instrument business C&EN tracks accounts for nearly 70% of the firm’s sales. In a late-September forecast, JEOL said it expects sales to rise nearly 2% in the fiscal year ending March 2018. JEOL and Bruker have been the only makers of large nuclear magnetic resonance instruments since Agilent withdrew from the business in 2014. In addition to NMR instruments, JEOL offers replacement NMR consoles and NMR probes. Last year, it introduced the Royal HFX, a probe intended to ease analysis of the large number of fluorine-containing drugs on the market.

R&D spending

All instrument makers ramped up investment in 2017.

Source: Company data

14 Spectris

▸  2017 instrument sales: $599 million

Sales increased 11% for the materials analysis instrument segment of England-based Spectris in 2017. The segment includes Particle Measuring Systems and Malvern Panalytical, consisting of the former Malvern Instruments and PANalytical, which Spectris decided to combine into one unit at the end of 2016. Asia accounted for the bulk of the sales boost, Spectris said in its year-end report. Sales to academia were weak across all regions, it added, and will continue to be muted in 2018, except in China. In January 2018, Spectris acquired Concept Life Sciences , a contract research organization serving pharmaceutical, agrochemical, and environmental customers, for more than $200 million. Like Thermo Fisher Scientific, which bought contract drugmaker Patheon in 2017, Spectris sees growth potential in the services sector. Spectris plans to incorporate Concept Life Sciences into the materials analysis segment.

15 Hitachi High-Technologies

▸  2017 instrument sales: $596 million

Hitachi High-Technologies is organized into four businesses. Three focus on industrial and electronic equipment. The fourth, which is tracked by C&EN, is a science and medical systems business that accounts for almost 10% of the firm’s annual revenues. Its portfolio includes analytical instruments such as liquid chromatographs, mass spectrometers, and spectrophotometers. The business also makes electron, focused beam, and atomic force microscopes. A third area of focus is clinical analyzers and lab automation systems. For its fiscal year ending in March 2018, Hitachi says strong demand for electron microscopes and analytical systems should increase sales more than 20%. Demand is strong in Asia, Europe, and the U.S., Hitachi says, but stagnant in its home market of Japan.

16 Illumina

▸  2017 instrument sales: $515 million

After a drop in 2016, Illumina’s instrument sales, which make up about 19% of total revenue, rose almost 10% in 2017. The leader in the gene sequencing market, Illumina expects to start shipping a new desktop sequencing unit shortly at a cost, it says, that will be affordable to any lab. The firm is increasing its emphasis on clinical-grade instruments and reagents, CEO Francis deSouza told investors at the end of January. In August, the firm said it would establish a new company, Verogen, with San Francisco-based venture capital firm Telegraph Hill Partners to provide Illumina’s sequencing technology to companies doing forensic casework. Among the instrument makers C&EN follows, Illumina devotes the highest percentage of its sales, nearly 20%, to research. In absolute terms, its $546 million in 2017 research spending is the second largest, coming after Thermo Fisher.

▸  2017 instrument sales: $508 million

As part of a restructuring effort, Nikon has cut more than 1,000 jobs and shifted its business segments. The reorganization refocused the firm on semiconductor lithography as sales of digital cameras decline. The restructuring also places Nikon’s research microscope business into a new health care segment. Formerly those microscopes were part of an instrument business that included industrial metrology tools. The shift drops Nikon’s place in C&EN’s ranking to number 17 from number 13 last year. The health care segment expects to report $508 million in sales for the fiscal year ending March 2018, accounting for nearly 8% of the Japanese firm’s overall sales.

18 Sartorius

▸   2017 instrument sales: $445 million

Sartorius, a bioprocessing and lab equipment firm, had a good 2017. The lab products and services division that C&EN tracks recorded sales growth of more than 21%. According to Sartorius, 14% of that growth came from recent acquisitions. The division itself accounted for 28% of Sartorius’s overall sales in 2017, up from 25% in 2016. The most significant acquisition in 2017 was of U.S.-based Essen BioScience, a maker of cell-based assays and instruments used for drug discovery and basic research. The $320 million purchase added about $60 million in revenues. For 2018, Sartorius predicts that lab products division sales will grow between 12 and 15%.

Olympus markets a variety of equipment for industrial and health-related markets. Its products include industrial microscopes and videoscopes, nondestructive test equipment, and X-ray fluorescence analyzers. The Olympus business that C&EN tracks is biological microscopes, which are intended to advance drug discovery and clinical pathology. The firm expects its biological microscopes business will contribute nearly 5% to its overall sales for the fiscal year ending in March 2018.

▸  2017 instrument sales: $338 million

Tecan has been growing through acquisitions. In March 2017, it acquired Pulssar Technologies, a maker of piston pumps used for pipetting tasks in the life sciences. In late 2015 it acquired Sias, a supplier of lab automation systems for liquid handling. Tecan classifies 62% of its sales as instruments. The remainder are in consumables, services, and spare parts, according to a presentation Tecan made at the J.P. Morgan Healthcare Conference last month.

CORRECTION: This story was updated on April 2, 2018, to correct the description of a photo. The photo, a close-up, depicts the ionization source in Waters’s Vion ion mobility spectrometry/quadrupole time-of-flight mass spectrometer, not a Thermo Fisher purge valve.

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10 free online tools for scientific research

 X min read 

As the landscape of scientific research evolves, the shift towards online tools has introduced a sea of resources that can profoundly impact the productivity and effectiveness of scientific endeavors.

The key is to identify tools that enhance your research without complicating your process.

While diving into this ocean of resources, there are several important things to look for:

• Ease of Use: Opt for tools with intuitive interfaces.
• Artificial Intelligence: Look for AI integration to automate and enhance research tasks.
• Data Security: Ensure compliance with the latest data security and privacy standards.
• Software Integration: Favor tools that offer seamless integration with existing systems.
• Accuracy: Verify that the tools provide precise and correct information.
• Free Access: Confirm that there’s a genuinely free offer, not just a trial period that requires future payment.

With these criteria in mind, let’s explore ten free online tools that could become indispensable for your scientific research.

1. Semantic Scholar

Powered by AI, Semantic Scholar is a free, nonprofit research tool that stands out for its smart search capabilities.

It sifts through millions of publications to bring you the most relevant and impactful studies, cutting down the time you’d typically spend on literature review.

With a focus on AI, Semantic Scholar offers personalized recommendations, citation summaries, and key phrase extractions that make keeping up with your field’s latest a breeze.

Visit Semantic Scholar

2. Connected Papers

Connected Papers offers a unique visual take on research, building an interactive graph that shows the connections between scientific papers.

It’s like having a bird’s-eye view of the research landscape, allowing you to trace the development of ideas and how they relate to one another. This can uncover pivotal papers that might otherwise slip through the cracks.

Visit Connected Papers

3. Scholarcy

Scholarcy is your AI-powered reading companion, making sense of complex academic papers by breaking them down into digestible summaries.

Imagine having the ability to absorb the core themes and conclusions of a dense, 30-page document in a matter of minutes. Scholarcy makes this a reality, highlighting the methodology, results, and discussions that are central to understanding the paper’s contribution to the field.

This tool is perfect for researchers who are pressed for time but need to stay ahead of the curve. With Scholarcy, you can easily grasp the essence of lengthy publications and build a knowledge base faster than ever.

Visit Scholarcy

4. Consensus

Imagine if you could quickly gauge the consensus of the scientific community on a particular topic. That’s exactly what Consensus aims to do.

Powered by the sophisticated GPT-4 model, Consensus operates as a dynamic search engine that delivers not just search results but a synthesized understanding of where the scientific agreement lies on complex subjects.

With its AI-driven analysis, it reviews multiple studies and delivers a consensus view, helping to inform your research stance.

It’s like a digital synthesis of expert opinions at your fingertips.

Visit Consensus

5. Research Rabbit

Research Rabbit is more than just a tool; it’s your research exploration partner. It helps you discover and organize literature in a personalized research landscape.

The magic of Research Rabbit lies in its ability to learn and adapt to your research behavior, suggesting not just content but also potential pathways your research could take.

It’s much like having a personal librarian who not only knows your research interests but also suggests connections you might not have considered, leading to innovative ideas and directions.

Visit Research Rabbit

6. Audemic.io

Audemic.io stands out in the digital research tools space by transforming the way we consume scientific literature. It leverages the power of audio to make research papers accessible in a format that’s perfect for the multitasking researcher.

Whether you’re commuting or running an experiment, Audemic.io ensures that you can keep up with the latest publications by listening, making the continuous learning process a seamless part of your daily routine.

Visit Audemic.io

Zotero revolutionizes the way researchers manage their references.

Zotero is a haven for anyone looking to organize their sources, offering an intuitive platform for collecting, organizing, and citing research materials. With it, you can easily create bibliographies and in-text citations in a variety of citation styles, which are essential for manuscript preparation.

Zotero holds the distinction of being the oldest tool on this list. Having stood the test of time since its inception in 2006, it proves that a tool does not require all the bells and whistles, or even AI technology, to remain relevant and useful in the fast-paced world of academic research.

Its continued popularity underscores the fact that reliability, ease of use, and a user-focused approach never go out of style.

Visit Zotero

8. Protocols.io

Protocols.io is an indispensable tool for researchers who understand that the devil is often in the details—particularly when it comes to experimental protocols. This platform allows for the creation, sharing, and collaborative refinement of protocols.

Not only does it provide a dynamic space for protocol management, but it also seamlessly integrates with SciNote —a comprehensive electronic lab notebook—allowing for an efficient transition from planning to execution.

Visit Protocols.io

9. Scite.ai

Scite.ai takes a novel approach to assessing the reliability of scientific papers.

Using a sophisticated AI, it analyzes citation contexts to provide “Smart Citations,” allowing researchers to see how a paper has been cited, and if its findings have been supported or contradicted.

This insight is crucial in gauging the impact and reliability of research findings , offering a new dimension to the citation analysis that goes beyond mere numbers.

Visit Scite.ai

10. SciNote ELN

Managing research data effectively is critical, and SciNote ELN is the online tool designed for this task.

It’s an electronic lab notebook that helps you keep your research data organized and secure. With features that support project management, team collaboration, and inventory tracking, SciNote is not just a digital notebook—it’s a central hub for managing all aspects of your research projects.

It’s designed to bring order to the complexity of research data, ensuring that every finding and experiment is documented comprehensively.

Visit SciNote ELN

Final Thoughts

In the current research landscape, these tools are more than conveniences; they’re necessities for staying current, connected, and creative in your work.

Whether you’re looking to manage data, streamline processes, or consume literature in innovative ways, the digital solutions available can significantly enhance the efficiency and impact of your research.

Each of these tools offers a unique angle on the research process, tailored to save time, foster collaboration, and enhance discovery.

By incorporating these into your workflow, you embrace a future where technology and science go hand in hand, creating a symbiosis that propels both forward.

Whether through AI-powered summaries or visual mapping of the literature, these tools embody the innovative spirit of the scientific community. By leveraging these resources, researchers can stand on the shoulders of the digital giants to reach new heights in their academic and professional pursuits.

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The instrument makers research.

Musical instrument making, especially of stringed instruments such as the violin, represents a tradition with a long history in Europe and America. The earliest instruments in Europe– the harp (or lyre) and the lute–were introduced from Asia. These instruments were primarily used to accompany singing before the Renaissance. Beginning in 1532, German and Spanish composers began writing music specifically for violins. In the middle of the sixteenth century, violins and their relatives were made by craftsmen who perfected the violin-making technique still in use today. The construction of a violin depends upon an important acoustical phenomenon. The function of its body in forming the characteristic timbre is not confined to picking up the vibrations of the bowed strings and to radiating them from a broader surface. The instrument adds timbre to the sound.

The first great violin makers, Gasparo Bertolotti (1542-1609) and Giovanni Paolo Maggini (1580-1632), lived in Italy. Almost at the same time, the city of Cremona became the world center of violin manufacture for a period of about one hundred years. Of course, the grand master, Antonio Stradivari (1640-1737) made violins for many years, continually altering his pattern. The Germans and the English began making violins in the mid-seventeenth century. France became known for its wonderful violin bow making. The violin developed first as a chamber musical instrument but was widely adapted for orchestra and nearly every other genre of music across Europe, including various folk genres.

Violins came to America and were often used in the earlier years as accompaniment for church music. About 1800 the first violin was manufactured in Bangor, Maine. This marked an increased interest in music around the state, not only in church, but also in singing schools which were organized in many towns throughout Maine. The Violin Maker’s association in the State of Maine was established in 1916 for the purpose of encouraging and promoting the art of violin making and was said to have been the first of its kind formed in America. It only lasted for nine years, but one of its members was the pioneer violin maker Leander M. Nute of Portland who made more than two hundred and seventy fine instruments prior to his death in 1925.

Today there are fewer but no less dedicated stringed instrument makers in Maine. Pauleena MacDougall is interviewing violin, violin bow, guitar, mandolin and harp makers around the state, from South Portland to Presque Isle. In addition, we will be inviting some of the instrument makers to the National Folk Festival in Bangor in August 23-24, 2003, to demonstrate how the work is done. Below are some excerpts from an interview with Jonathan Cooper, violin maker from South Gorham, Maine:

PM: Is there a difference between the German way of making violins and the Italian? JC: There are differences. A lot of the differences have to do with the way you think of the building process. When its all said and done you’re making something that’s almost precisely the same as far as most people would tell. But there are big differences in the way an instrument sounds. I mean, I have my own theory as to why–the German attention to perhaps, detail, and the German attention to engineering and their very precise way and perhaps the Italians more doing things a little more individualistically, more of a flair to what they do. For me the big difference is the Italian is much more individual, many people would say its perhaps, looser, its not done on the same level of precision although I don’t think it has to be. But you could find German makers who are not quite as precise and Italian makers who are more precise–it goes back and forth. PM: So there’s no real distinct style difference–more of a gradation? JC: Nothing that a violin maker–violin makers would discern the difference–nobody else would. Musicians to an extent would know the difference. I happen to like the idea–and I have been at it quite a while now, but I’m still finding there’s just a lot of insight to be had as to what the frame of mind was when a person was doing it originally. This is important to the sound and the way the instrument comes out. I’ll say one thing, the Italians were really the people who in many ways perfected this as we see it now. And the Germans had great success in the mass production–their methods in producing instruments filled a huge need almost at the beginning when the violin was invented it became very successful as an instrument and there was an enormous need for it, and you couldn’t do it with two guys working in a workshop. You couldn’t produce the volume–you’d have to have a violin maker for every hundred people. It just wouldn’t work that way, and it was expensive. The Germans and the French came up with some very good methods for making very good instruments on a large scale. And I think that’s one of the big differences. The Italians never got into commercial production. Their industry always stayed sort of as a one person shop sort of thing and where the Germans would often have whole cities making violins. PM: Very interesting. So after you left Italy, where did you go? JC: I worked in Germany for a while, in Hamburg. And then I was there for almost a year but then I came back to Maine. I lived in Portland and had a shop in Portland. PM: And were you in Portland a long time? JC: That would have been 1983-84 when I had a shop there. I had a regular retail violin shop. Doing repairs, selling strings, making some instruments, until I moved to my current location in 1990. And in that time I changed what I do from being diversified and doing repairs and things to just making violins. And that’s all I’ve been doing for awhile. PM: How did you develop your market for your violins? JC: Mostly by word of mouth. You know, you make an instrument for one person and then another person sees it. I knew people from when I was playing so I would show it to them. It’s really not a very big world, it’s a small world and you pretty much know a lot of people in it. So I often would either someone will call me and want–they know something about one of my instruments and they’ll be interested or I will make instruments just to make them, since I want to make them, and then I’ll consign them to different shops around the country. Who then resell them to somebody else. PM: So, you don’t do any advertising at all, or you do a little? JC: I do a little bit. A couple of very small ads but I just recently started running, but its not–its mostly that you know everybody. I did a lot of dealing in old instruments and so most of the people in the trade who have shops throughout the country know me, so that helps, because I know who these people are, from dealing with them and I know they’re interested. PM: Let me ask you a little bit about the process. I guess starting out with wood. What kind of wood do you like and are there a very limited number of woods that you use, and where do they come from? JC: That’s a good question. A lot of the materials that we use now were figured out many years ago. So in terms of the materials that you use, we are not experimenting. We’re looking at the quality of the materials and the kind of materials. You can see by looking at old instruments that are successful and sound good you can get a certain amount of knowledge as to what works and what doesn’t. Primarily we use maple for the back and sides for violins, violas and cellos. PM: Do you know what kind of maple? JC: Yes, its often figured, and often has a recognizable what you call curl to it or pattern which is the way the wood grows. No one knows exactly why, some people say it is genetically that way based on the fact that you’ll find a lot of trees in a certain area that will have that figure. I think that may actually have been more ornamental than anything else because for tone I don’t think it helps any either way, its sort of an indifferent kind of thing. We tend to use wood that has a certain specific gravity or weight because a musical instrument has to be both strong and light. It can’t be too light, it can’t be too strong. So by the time you get to the point at which you’ve got the instrument finished, those are within very close tolerances. So there are species of maple which grow all over the world that have been tried or seen, some come from China and other places that are too heavy. But the wood that we predominantly use is maple that comes from south Germany, Yugoslavia, Bosnia was one source of it. I use maple that comes from the United States for some instruments. PM: Where in the United States? JC: Maine. I’ve got wood in Maine. About six or seven years ago I got a whole tree which produced a lot of wood. A violin maker does not use a lot of wood, the wood in a violin is 10-15 inches long and an inch thick and you’re using that much wood every month. So you’re going through about 14 board feet of wood a year. Guys will nail that up in two minutes. PM: Right. JC: Our demands aren’t great. They’re very specific so the wood is quite expensive and it has to be very highly selective. PM: What species of maple? JC: Red maple, its hard to know unless you go out and see the tree standing with the leaves on and you know where it came from. You can do the more detailed analysis of the wood which can be done, but when you are looking to buy wood, or looking to acquire wood, I usually just hold it in my hand and look. PM: Do you purchase wood from people who specifically sell wood to violin makers? JC: There is a specific industry that produces wood for violin makers. And it runs the gamut from a very sophisticated operation in southern Germany that has been supplying wood to the trade for the past three hundred years from certain areas, all the way to a perhaps buying 2 or 3 pieces of wood from a violin maker who died and saved his best wood until he was dead. And sometimes I will literally–I mean I’m always looking at wood. I’ve gone into the woodworkers’ store in Boston to get some drill bits and they sell wood and I saw some wood standing in the corner, which I bought. It wasn’t cut for the purpose of making violins and out of 10,000 board feet that they cut up there is just one board that was cut the right way and is the right kind of wood–at $1.20 a foot I couldn’t pass it up–you know vs. $200…. PM: Okay, so you mentioned spruce. The spruce is for the top. JC: The maple is for the back, sides and scroll, the spruce is always for the top. Why they chose spruce– I can see some reasons why–you see it in instruments that predate the violin and my suspicion is–well, the obvious reason is the top has certain structural requirements because it has sound holes and you need wood that is very strong longitudinally. Whereas maple is has flexibility on both axis. Spruce has become the choice, and spruce again, you want it to be fairly light, it has to be clear also. We use other species in violin making, such as poplar sometimes for violas or cellos. Sometimes I’ve been using sycamore, lately, American sycamore. There is some experimentation but not much.

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Transparency on scientific instruments

Carsten bergenholtz.

1 Department of Management, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark

Samuel C MacAulay

2 UTS Business School, University of Technology Sydney, Sydney, NSW, Australia

Christos Kolympiris

3 School of Management, University of Bath, Bath, UK

4 School of Biomedical Sciences, Queensland University of Technology, Brisbane, Qld, Australia

Scientists and commercial scientific instrument makers have a shared incentive against discloseing an instrument maker's contributions to research. Stricter rules to encourage reporting of such collaboration would help to improve transparency and reproducibility.

Scientific instruments are at the heart of the scientific process, from 17 th ‐century telescopes and microscopes, to modern particle colliders and DNA sequencing machines. Nowadays, most scientific instruments in biomedical research come from commercial suppliers 1 , 2 , and yet, compared to the biopharmaceutical and medical devices industries, little is known about the interactions between scientific instrument makers and academic researchers. Our research suggests that this knowledge gap is a cause for concern.

It is the norm—and usually a requirement—that scientists mention instruments and their suppliers in the materials and methods sections of research articles, since their colleagues rely on this information to replicate or adapt their experiments. However, as the production and distribution of instruments have become increasingly commercialized 3 , there are signs that this information is no longer sufficient. For example, research conducted by one of us (C.B.) revealed that some scientific instrument makers preferred not to appear as co‐authors on manuscripts—even when their employees contributed significantly to it 1 . It was believed that a manuscript would appear more credible if the company's employees did not appear as co‐authors, thus enhancing the marketing value of their instrument.

To complement this study, we conducted two surveys of academic researchers in the USA and EU to gauge how they judge information sources for scientific instruments [preprint: 4 ]. The responses from almost 1,000 academic researchers revealed a marked distrust in manuscripts co‐authored by commercial makers of scientific instruments. The first survey inquired whether academic researchers consider information on instruments important, while the second survey focused on the perceived reliability of different information sources. Combined, they provide insight into how credible academic researchers find information on scientific instruments in peer‐reviewed manuscripts. As Fig ​ Fig1 1 shows, academics discount both the importance and the reliability of information on instruments in peer‐reviewed manuscripts co‐authored by scientific instrument firm employees—even when the firm's instrument is not mentioned in the manuscript. When directly comparing the reliability of information on instruments in manuscripts authored by someone from the mentioned instrument firm or not, the difference was statistically significant and substantial. The same perceptions were evident in all scientific fields surveyed [preprint: 4 ].

Illustration of how important and reliable respondents, indicated in percent on the y ‐axis, consider information on scientific instruments to be in peer‐reviewed publications in general and various subcategories ( x ‐axis).

We argue that these perceptions create an, as yet underappreciated, incentive for non‐disclosure and complementary tactics by scientific instrument makers. This pattern of incentives mirrors those that have generated controversial practices, such as ghostwriting and hidden sponsorship 5 . The revelations of these practices in the biopharmaceutical industry likely fueled a Zeitgeist of inherent distrust in firm co‐authorship by academic researchers and scientific instrument firms alike.

From a commercial perspective, it is not surprising that some companies circumvent the perceived reduced credibility by not allowing employees to be listed as co‐authors, irrespective of whether they contributed significantly to the published work 1 . It boosts the credibility of the manuscript and, presumably, also the commercial instruments employed to generate the research data. Revelations from the biopharmaceutical and medical devices industries have demonstrated that such concerns are valid. For example, a range of studies showed how commercial sponsorship of academic research on drugs shaped the likelihood of reporting results 6 and influenced the perception of the research 7 .

Critically, non‐disclosure not only leaves readers unable to judge potential conflicts of interests, but it also makes replication more difficult. More transparency on if and how companies were involved in the experiments could mitigate these risks, as could more detailed information in materials and methods sections, such as instrument settings and downstream data analysis.

In order to assess how much information authors are asked to provide about instruments, we carried out an informal analysis of the guidelines of the 20 most cited journals, as measured by the Google Scholar h5‐index in the categories “Health & Medical Sciences”, “Life Sciences & Earth Sciences”, and “Chemical & Material Sciences”. Almost none of the guidelines require the sort of detailed information about instrument settings and procedures required to allow others to replicate the experiment. Moreover, with one notable exception, none of these journals explicitly address the issue of contributions by instrument makers [preprint: 4 ]—be they financial or technical. Only the guidelines by the American Medical Association (AMA) require disclosing financial contribution, specifying that if an instrument was provided free of charge (a 100% discount), it should be made explicit [preprint: 4 ].

To illustrate the disclosure dilemma facing scientists, it may be useful to imagine a situation in which an academic researcher received a 20% discount on an instrument and considerable assistance from the company with generating and analyzing data from said instrument. The academic publishes the results in a peer‐reviewed journal, and the manuscript is cited multiple times. A strict interpretation of journal guidelines would not require the scientist to disclose either the financial benefit or the involvement of the company in data generation and interpretation. Moreover, since being affiliated with a commercial company seems to influence how fellow academic researchers value the manuscript, the academic and the instrument maker have a shared incentive against disclosing pertinent facts.

Public debate and guidelines or policies by academic journals have contributed significantly to tackling non‐disclosure issues in pharmaceutical research 3 . More recently, public debate on the reproducibility of the results from biomedical research led to further changes in both norms and journal guidelines 8 , 9 . We argue that there should be equal attention to commercial instruments that are central to scientific research. As the scientific instrument industry is increasingly dominated by large corporations and as expensive instruments have become commonplace in academic laboratories 10 , the debate on reproducibility of and transparency in research should address the issue of how and when researchers should disclose the involvement of instrument firms in research. Each day that goes by without change further undermines the transparency that is required for reproducibility and scientific progress.

Acknowledgements

This work was supported by a Thiess Fellowship (to S.M.) and a QUT Vice‐Chancellor's Senior Research Fellowship (to I.S.).

EMBO Reports (2018) 19 : e45853 [ Google Scholar ]

Research Instrument

Ai generator.

A research instrument is a tool or device used by researchers to collect, measure, and analyze data relevant to their study. Common examples include surveys, questionnaires , tests, and observational checklists. These instruments are essential for obtaining accurate, reliable, and valid data, enabling researchers to draw meaningful conclusions and insights. The selection of an appropriate research instrument is crucial, as it directly impacts the quality and integrity of the research findings.

What is a Research Instrument?

A research instrument is a tool used by researchers to collect and analyze data. Examples include surveys, questionnaires, and observation checklists. Choosing the right instrument is essential for ensuring accurate and reliable data.

Examples of Research Instruments

• Surveys: Structured questionnaires designed to gather quantitative data from a large audience.
• Questionnaires: Sets of written questions used to collect information on specific topics.
• Interviews: Structured or semi-structured conversations used to obtain in-depth qualitative data.
• Observation Checklists: Lists of specific behaviors or events that researchers observe and record.
• Tests: Standardized exams used to assess knowledge, skills, or abilities.
• Scales: Tools like Likert scales to measure attitudes, perceptions, or opinions.
• Diaries: Participant logs documenting activities or experiences over time.
• Focus Groups: Group discussions facilitated to explore collective views and experiences.

Examples of a Quantitative Research Instruments

• Structured Surveys: These are detailed questionnaires with predefined questions and response options, designed to collect numerical data from a large sample. They are often used in market research and social sciences to identify trends and patterns.
• Standardized Tests: These are assessments that measure specific knowledge, skills, or abilities using uniform procedures and scoring methods. Examples include IQ tests, academic achievement tests, and professional certification exams.
• Closed-Ended Questionnaires: These questionnaires contain questions with a limited set of response options, such as multiple-choice or yes/no answers. They are useful for gathering specific, quantifiable data efficiently.
• Rating Scales: These tools ask respondents to rate items on a fixed scale, such as 1 to 5 or 1 to 10. They are commonly used to measure attitudes, opinions, or satisfaction levels.
• Structured Observation Checklists: These checklists outline specific behaviors or events that researchers observe and record in a systematic manner. They are often used in studies where direct observation is needed to gather quantitative data.
• Statistical Data Collection Tools: These include various instruments and software used to collect and analyze numerical data, such as spreadsheets, databases, and statistical analysis programs like SPSS or SAS.
• Likert Scales: A type of rating scale commonly used in surveys to measure attitudes or opinions. Respondents indicate their level of agreement or disagreement with a series of statements on a scale, such as “strongly agree” to “strongly disagree.”

Examples of a Qualitative Research Instruments

• Open-Ended Interviews: These interviews involve asking participants broad, open-ended questions to explore their thoughts, feelings, and experiences in depth. This method allows for rich, detailed data collection.
• Focus Groups: A small, diverse group of people engage in guided discussions to provide insights into their perceptions, opinions, and attitudes about a specific topic. Focus groups are useful for exploring complex behaviors and motivations.
• Unstructured Observation: Researchers observe participants in their natural environment without predefined criteria, allowing them to capture spontaneous behaviors and interactions in real-time.
• Case Studies: In-depth investigations of a single individual, group, event, or community. Case studies provide comprehensive insights into the subject’s context, experiences, and development over time.
• Ethnographic Studies: Researchers immerse themselves in the daily lives of participants to understand their cultures, practices, and perspectives. This method often involves long-term observation and interaction.
• Participant Diaries: Participants keep detailed, personal records of their daily activities, thoughts, and experiences over a specific period. These diaries provide firsthand insights into participants’ lives.
• Field Notes: Researchers take detailed notes while observing participants in their natural settings. Field notes capture contextual information, behaviors, and interactions that are often missed in structured observations.
• Narrative Analysis: This method involves analyzing stories and personal accounts to understand how people make sense of their experiences and the world around them.
• Content Analysis: Researchers systematically analyze textual, visual, or a content to identify patterns, themes, and meanings. This method is often used for analyzing media, documents, and online content.
• Document Analysis: Researchers review and interpret existing documents, such as reports, letters, or official records, to gain insights into the context and background of the research subject.

Characteristics of a Good Research Instrument

• Validity: A good research instrument accurately measures what it is intended to measure. This ensures that the results are a true reflection of the concept being studied.
• Reliability: The instrument produces consistent results when used repeatedly under similar conditions. This consistency is crucial for the credibility of the research findings.
• Objectivity: The instrument should be free from researcher bias, ensuring that results are based solely on the data collected rather than subjective interpretations.
• Sensitivity: The instrument is capable of detecting subtle differences or changes in the variable being measured, allowing for more nuanced and precise data collection.
• Practicality: It is easy to administer, score, and interpret. This includes being time-efficient, cost-effective, and user-friendly for both researchers and participants.
• Ethical Considerations: The instrument respects the rights and confidentiality of participants, ensuring informed consent and protecting their privacy throughout the research process.
• Comprehensiveness: It covers all relevant aspects of the concept being studied, providing a complete and thorough understanding of the research topic.
• Adaptability: The instrument can be modified or adapted for different contexts, populations, or research settings without losing its effectiveness.
• Clarity: The questions or items in the instrument are clearly worded and unambiguous, ensuring that participants understand what is being asked without confusion.
• Cultural Sensitivity: The instrument is appropriate for the cultural context of the participants, avoiding language or content that may be misinterpreted or offensive.

Research Instrument Questionnaire

A questionnaire is a versatile and widely used research instrument composed of a series of questions aimed at gathering information from respondents. It is designed to collect both quantitative and qualitative data through a mix of open-ended and closed-ended questions. Open-ended questions allow respondents to express their thoughts in their own words, providing rich, detailed insights, while closed-ended questions offer predefined response options, facilitating easier statistical analysis. Questionnaires can be administered in various formats, including paper-based, online, or via telephone, making them accessible to a wide audience and suitable for large-scale studies.

The design of a questionnaire is crucial to its effectiveness. Clear, concise, and unbiased questions are essential to ensure reliable and valid results. A well-crafted questionnaire minimizes respondent confusion and reduces the risk of biased answers, which can skew data. Moreover, the order and wording of questions can significantly impact the quality of the responses. Properly designed questionnaires are invaluable tools for a range of research purposes, from market research and customer satisfaction surveys to academic studies and social science research. They enable researchers to gather a broad spectrum of data efficiently and effectively, making them a cornerstone of data collection in many fields.

Research instrument Sample Paragraph

A research instrument is a vital tool used by researchers to collect, measure, and analyze data from participants. These instruments vary widely and include questionnaires, surveys, interviews, observation checklists, and standardized tests, each serving distinct research needs. For example, questionnaires and surveys are commonly employed to gather quantitative data from large groups, providing statistical insights into trends and patterns. In contrast, interviews and focus groups are used to delve deeper into participants’ experiences and perspectives, yielding rich qualitative data. The careful selection and design of a research instrument are crucial, as they directly impact the accuracy, reliability, and validity of the collected data,

How to Make Research Instrument

Creating an effective research instrument involves several key steps to ensure it accurately collects and measures the necessary data for your study:

1. Define the Research Objectives

• Identify the Purpose : Clearly outline what you aim to achieve with your research.
• Specify the Variables : Determine the specific variables you need to measure.

2. Review Existing Instruments

• Literature Review : Look at existing studies and instruments used in similar research.
• Evaluate Suitability : Assess if existing instruments can be adapted for your study.

3. Select the Type of Instrument

• Choose the Format : Decide whether a survey, questionnaire, interview guide, test, or observation checklist best fits your needs.
• Determine the Method : Consider whether your data collection will be qualitative, quantitative, or mixed-methods.

4. Develop the Content

• Draft Questions or Items : Write questions that align with your research objectives and variables.
• Ensure Clarity and Relevance : Make sure each question is clear, concise, and directly related to the research objectives.
• Use Simple Language : Avoid jargon to ensure respondents understand the questions.

5. Validate the Instrument

• Expert Review : Have experts in your field review the instrument for content validity.
• Pilot Testing : Conduct a pilot test with a small, representative sample to identify any issues.

6. Refine the Instrument

• Revise Based on Feedback : Modify the instrument based on feedback from experts and pilot testing.
• Check for Reliability : Ensure the instrument consistently measures what it is supposed to.

7. Finalize the Instrument

• Create Instructions : Provide clear instructions for respondents on how to complete the instrument.
• Format Appropriately : Ensure the layout is user-friendly and the instrument is easy to navigate.

8. Implement and Collect Data

• Administer the Instrument : Distribute your instrument to the target population.
• Monitor Data Collection : Ensure the data collection process is conducted consistently.

FAQ’s

How do you choose a research instrument.

Select based on your research goals, type of data needed, and the target population.

What is the difference between qualitative and quantitative research instruments?

Qualitative instruments collect non-numerical data, while quantitative instruments collect numerical data.

Can you use multiple research instruments in one study?

Yes, using multiple instruments can provide a more comprehensive understanding of the research problem.

How do you ensure the reliability of a research instrument?

Test the instrument multiple times under the same conditions to check for consistent results.

What is the validity of a research instrument?

Validity refers to how well an instrument measures what it is intended to measure.

How can you test the validity of a research instrument?

Use methods like content validity, criterion-related validity, and construct validity to test an instrument.

What is a pilot study?

A pilot study is a small-scale trial run of a research instrument to identify any issues before the main study.

Why is a pilot study important?

It helps refine the research instrument and improve its reliability and validity.

What is an unstructured interview?

An unstructured interview allows more flexibility, with open-ended questions that can adapt based on responses.

What is the role of observation in research?

Observation allows researchers to collect data on behaviors and events in their natural settings.

Text prompt

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Boris Jardine and Joshua Nall, October 2017

Introduction

This guide is aimed at researchers who want to start working on an instrument, or a group or general class of instruments, and are in need of example studies , collections databases and associated resources , and an introductory reading list .

First, what kind of a primary source is an instrument?

• An instrument is like a text in that it can be 'read', often literally if it has inscriptions; but an instrument is unlike a text in that its materiality is essential to its story (Fig. 1).

• Collections of instruments are like archives, in that they form the basis of historical research, preserving (in a highly selective way) evidence of what was actually in use; but instrument collections are unlike archives in that instruments were not normally made to live in cabinets and store-rooms, so they have been uprooted from their context (Fig. 2).

• Instruments are like images, in that they can have symbolic meanings and aesthetic value; but they are unlike images insofar as their utility is also a part of their meaning, and sometimes of their aesthetic and even symbolic meaning (Fig. 3).

Studying an instrument typically requires close – almost forensic – analysis of the object itself. Are there marks of use? How has it been kept? Are there inscriptions revealing provenance? What can be said about the engraving, or the method of construction? It can also require detective work to unearth wider contexts of manufacture and use. Are there records of who made, sold, used, or collected it? Can reports, patents, or correspondence help shed light on its life history?

This may all sound rather daunting, but fear not: the Whipple Museum offers a wealth of resources and support for students and researchers interested in working with material culture. In the Museum itself you will find numerous objects of all kinds, with plenty of information about how they were used, why they survived, and what they can tell us about the history of science. You will also find displays and essays, curated and written by staff and students in HPS. Staff in the Museum are always happy to discuss potential objects and topics with students, and its curators have extensive experience supervising instrument research. Relevant course managers can also direct students to a variety of people in the HPS Department and beyond with expertise in studying material culture.

For capsule examples of research into specific instruments see the Whipple Museum's invaluable 'Explore' website.

See also the many articles in Liba Taub & Frances Willmoth (eds), The Whipple Museum of the History of Science: Instruments and Interpretations, to Celebrate the 60th Anniversary of R.S. Whipple's Gift to the University of Cambridge (Cambridge: Whipple Museum of the History of Science, 2006).

Comparative and contextual work is also essential. The remainder of this guide offers outline listings for collections and literature to help you with your research.

Example studies

The Whipple Museum's collection is unusually well-studied. Some of the papers that have resulted from these investigations include:

• The eighteen chapters in Part II of: Liba Taub & Frances Willmoth (eds), The Whipple Museum of the History of Science: Instruments and Interpretations, to Celebrate the 60th Anniversary of R.S. Whipple's Gift to the University of Cambridge (Cambridge: Whipple Museum of the History of Science, 2006)
• Melanie Keene, '"Every boy & girl a scientist": Instruments for children in interwar Britain', Isis 98 (2007), 266–289
• Katie Taylor, 'Mogg's celestial sphere (1813): The construction of polite astronomy', Studies in History and Philosophy of Science 40 (2009), 360–371
• Boris Jardine, 'Between the Beagle and the barnacle: Darwin's microscopy, 1837–1854', Studies in History and Philosophy of Science 40 (2009), 382–395
• Robin Wolfe Scheffler, 'Interests and instrument: A micro-history of object Wh.3469 (X-ray powder diffraction camera, ca. 1940)', Studies in History and Philosophy of Science , 40 (2009), 396–404
• Michael J. Barany, 'Great Pyramid Metrology and the Material Politics of Basalt', Spontaneous Generations 4 (2010), 45–60
• Seb Falk, 'The scholar as craftsman: Derek de Solla Price and the reconstruction of a medieval instrument', Notes and Records of the Royal Society 68 (2014), 111–134
• David E. Dunning, 'What Are Models For? Alexander Crum Brown's Knitted Mathematical Surfaces', Mathematical Intelligencer 37 (2015), 62–70
• James Poskett, 'Sounding in Silence: Men, Machines and the Changing Environment of Naval Discipline, 1796–1815', British Journal for the History of Science 48 (2015), 213–232
• Joshua Nall & Liba Taub, 'Three-Dimensional Models', in: Bernard Lightman (ed.), A Companion to the History of Science  (Chichester: Wiley Blackwell, 2016), pp. 572–586
• Joshua Nall & Liba Taub, 'Selling by the book: British scientific trade literature after 1800', in A.D. Morrison-Low, Sara J. Schechner, & Paolo Brenni (eds), How Scientific Instruments Have Changed Hands (Leiden: Brill, 2016), pp. 21–42
• Boris Jardine, Joshua Nall, & James Hyslop, 'More Than Mensing? Revisiting the Question of Fake Scientific Instruments', Bulletin of the Scientific Instrument Society , No. 132 (March 2017), pp. 22–29

Collections

Familiarity with local, national, and international collections is important for a number of reasons: it provides a rough knowledge of what sorts of objects survive, it gives a sense of the geographical distribution of objects, and – like a good bibliographic knowledge – it means you won't miss anything, and will always have more resources for your research.

A key but now somewhat out of date resource for collections in Britain is M. Holbrook, et al., Science Preserved (London, 1992) [Whipple classmark: REF (DIR 16)].

The main instrument collections in Britain, in addition to the Whipple, are:

• Museum of the History of Science, Oxford
• The Science Museum, London
• National Maritime Museum, London
• The National Museums, Scotland
• The British Museum

Other collections with good online resources include:

• Adler Planetarium, Chicago
• Harvard University, Collection of Historical Scientific Instruments
• Musée des arts et metiers, Paris
• Museo Galileo, Florence
• Museum Boerhaave, Leyden
• The Smithsonian Institution, Washington DC
• UMAC's invaluable international survey of university collections

There are also significant holdings at Utrecht, Geneva, and Munich, and smaller collections in local museums and (especially) university collections around the world. The database 'Europeana' searches across many European collections.

Reading list

The Scientific Instrument Commission has a number of bibliographies , beginning with an exceptionally useful general survey in 1997 (see also the 1998 supplement ).

The best way in to instrument studies is to consult the various special journal issues that have appeared over the years:

• Osiris , 'Instruments' (1994)
• Journal for the History of Collections , 'Origins and Evolution of Collecting Scientific Instruments' (1995)
• Studies in History and Philosophy of Science , 'Objects, Texts and Images in the History of Science' (2007)
• Studies in History and Philosophy of Science , 'On Scientific Instruments' (2009)
• Isis , 'The History of Scientific Instruments' (2011)

The Brill series 'Scientific Instruments and Collections' contains some essential works.

The relevant Whipple Classmark is N: this is well worth browsing. Some of the key historical works and collections of essays include:

• R.G.W. Anderson, J.A. Bennett & W.F. Ryan (eds), Making Instruments Count (Aldershot: Variorum, 1993)
• Davis Baird, Thing Knowledge: A Philosophy of Scientific Instruments (Berkeley: University of California Press, 2004)
• Marie-Noëlle Bourguet, Christian Licoppe, & Heinz Otto Sibum (eds), Instruments, Travel and Science: Itineraries of Precision from the Seventeenth to the Twentieth Century (New York: Routledge, 2002)
• Robert Bud & Susan E. Cozzens (eds), Invisible Connections: Instruments, Institutions, and Science (Bellingham: SPIE Optical Engineering Press, 1992)
• Soraya de Chadarevian & Nick Hopwood (eds), Models: The Third Dimension of Science (Stanford: Stanford University Press, 2004)
• Adriana Craciun & Simon Schaffer (eds), The Material Cultures of Enlightenment Arts and Sciences (London: Palgrave Macmillan, 2016)
• Silvia De Renzi, Instruments in Print: Books from the Whipple collection (Cambridge: Whipple Museum of the History of Science, 2000)
• Peter Heering & Roland Wittje (eds), Learning by Doing: Experiments and Instruments in the History of Science Teaching (Stuttgart: Franz Steiner Verlag, 2011)
• Bernward Joerges & T. Shinn (eds), Instrumentation between Science, State and Industry (Dordrecht: Kluwer, 2001)
• Ursula Klein (ed.), Tools and Modes of Representation in the Laboratory Sciences (Dordrecht: Kluwer, 2001)
• Sachiko Kusukawa & Ian Maclean (eds), Transmitting Knowledge: Words, Images, and Instruments in Early Modern Europe (Oxford: Oxford University Press, 2006)
• Bernard Lightman (ed.), A Companion to the History of Science  (Chichester: Wiley Blackwell, 2016), Part IV: 'Tools of Science'
• Fraser Macdonald & Charles Withers (eds), Geography, Technology and Instruments of Exploration (Surrey: Ashgate, 2015)

The canonical reference texts and synoptic histories include:

• R.G.W. Anderson, et al., Handlist of Scientific Instrument-Makers' Trade Catalogues (Edinburgh: National Museums of Scotland, 1990)
• S.A. Bedini, Early American Scientific Instruments and their Makers (Washington DC: Museum of History and Technology, Smithsonian Institution, 1964)
• J.A. Bennett, The Divided Circle: A History of Instruments for Astronomy, Navigation and Surveying (Oxford: Phaidon, 1987)
• J.E. Burnett & A.D. Morrison-Low, Vulgar & Mechanick: The Scientific Instrument Trade in Ireland, 1650–1921 (Edinburgh: National Museums of Scotland, 1989)
• D.J. Bryden, Scottish Scientific Instrument Makers (Edinburgh: Royal Scottish Museum, 1972)
• R. Bud and D. Warner (eds), Instruments of Science: An Historical Encylopedia (New York and London: National Museum of American History, Smithsonian Institution and The Science Museum, 1998)
• R. Calvert, Scientific Trade Cards in the Science Museum Collection (London: HMSO, 1971)
• G. Clifton, Directory of British Scientific Instrument Makers 1550–1851 (London: National Maritime Museum, 1995)
• M. Daumas, Scientific Instruments in the Seventeenth and Eighteenth Centuries Their Makers (London: Batsford, 1972)
• P.R. de Clercq, Nineteenth-Century Scientific Instruments and their Makers (Leiden: Museum Boerhaave, 1985)
• E.G.R. Taylor, Mathematical Practitioners of Tudor and Stuart England (Cambridge: CUP, 1954)
• E.G.R. Taylor, Mathematical Practitioners of Hanoverian England (Cambridge: CUP, 1966)
• A.J. Turner, Early Scientific Instruments, Europe 1400–1800 (London: Sotheby's, 1987)
• G.L'E. Turner, Nineteenth-Century Scientific Instruments (London: Sotheby's, 1983)
• G.L'E. Turner, Elizabethan Instrument Makers: The Origins of the London Trade in Precision Instrument Making (Oxford: Oxford University Press, 2000)
• E. Zinner, Deutsches und Niederländische Astronomische Instrumente der 11.–18 Jahrhunderts (Munich: Becksche Verlagsbuchhandlung, 1956)

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9 Best Examples of Research Instruments in Qualitative Research Explained

Introduction.

Qualitative research is a valuable approach that allows researchers to explore complex phenomena and gain in-depth insights into the experiences and perspectives of individuals. In order to conduct qualitative research effectively, researchers often utilize various research methodologies and instruments. These methodologies and instruments serve as tools to collect and analyze data, enabling researchers to uncover rich and nuanced information.

In this article, we will delve into the world of qualitative research instruments, specifically focusing on research instrument examples. We will explore the different types of qualitative research instruments, provide specific examples, and discuss the advantages and limitations of using these instruments in qualitative research. By the end of this article, you will have a comprehensive understanding of the role and significance of research instruments in qualitative research.

Goals of Research Instruments in Qualitative Research

Qualitative research instruments are tools that researchers use to collect and analyze data in qualitative research studies. These instruments help researchers gather rich and detailed information about a particular phenomenon or topic.

One of the main goals of qualitative research is to understand the subjective experiences and perspectives of individuals. To achieve this, researchers need to use instruments that allow for in-depth exploration and interpretation of data. Qualitative research instruments can take various forms, including interviews, questionnaires, observations, and focus groups. Each instrument has its own strengths and limitations, and researchers need to carefully select the most appropriate instrument for their study objectives.

Exploring qualitative research instruments involves understanding the characteristics and features of each instrument, as well as considering the research context and the specific research questions being addressed. Researchers also need to consider the ethical implications of using qualitative research instruments, such as ensuring informed consent and maintaining confidentiality and anonymity of participants.

Examples of Qualitative Research Instruments

Qualitative research instruments are tools used to collect data and gather information in qualitative research studies. These instruments help researchers explore and understand complex social phenomena in depth. There are several types of qualitative research instruments that can be used depending on the research objectives and the nature of the study.

Interviews are one of the most commonly used qualitative research instruments. They involve direct communication between the researcher and the participant, allowing for in-depth exploration of the participant’s experiences, perspectives, and opinions. Interviews can be structured, semi-structured, or unstructured , depending on the level of flexibility in the questioning process. They involve researchers asking open-ended questions to participants to gather in-depth information and insights. Interviews can be conducted face-to-face, over the phone, or through video conferencing.

Focus Groups

Focus groups are another example of qualitative research instrument that involves a group discussion led by a researcher or moderator. Participants in a focus group share their thoughts, ideas, and experiences on a specific topic. This instrument allows for the exploration of group dynamics and the interaction between participants. It also allow researchers to gather multiple perspectives and generate rich qualitative data.

Observations

Observations are a powerful qualitative research instrument that involves systematic and careful observation of participants in their natural settings. This type of qualitative research instrument allows researchers to gather data on behavior, interactions, and social processes. Observations can be participant observations, where the researcher actively participates in the setting, or non-participant observations, where the researcher remains an observer.

Document Analysis

Document analysis is a qualitative research instrument that involves the examination, analyzation and interpretation of written or recorded materials such as documents, texts, audio/video recordings or other written materials. Researchers analyze documents to gain insights into social, cultural, or historical contexts, as well as to understand the perspectives and meanings embedded in the documents.

Visual Methods

Visual methods, such as photography, video recording, or drawings, can be used as qualitative research instruments. These methods allow participants to express their experiences and perspectives visually, providing rich and nuanced data. Visual methods can be particularly useful in studying topics related to art, culture, or visual communication.

Diaries or Journals

Diaries or journals can be used as qualitative research instruments to collect data on participants’ thoughts, feelings, and experiences over a period of time. Participants record their daily activities, reflections, and emotions, providing valuable insights into their lived experiences.

While surveys are commonly associated with quantitative research, they can also be used as qualitative research instruments. Qualitative surveys typically include open-ended questions that allow participants to provide detailed responses. Surveys can be administered online, through interviews, or in written form.

Case Studies

Case studies are in-depth investigations of a particular individual, group, or phenomenon. They involve collecting and analyzing qualitative data from various sources such as interviews, observations, and document analysis. Case studies provide rich and detailed insights into specific contexts or situations.

Ethnography

Ethnography is a qualitative research instrument that involves immersing researchers in a particular social or cultural group to observe and understand their behaviors, beliefs, and practices. Ethnographic research often includes participant observation, interviews, and document analysis.

These are just a few examples of qualitative research instruments. Researchers can choose the most appropriate data collection method or combination of methods based on their research objectives, the nature of the research question, and the available resources.

Advantages of Using Qualitative Research Instruments

Gathering in-depth and detailed information.

Qualitative research instruments offer several advantages that make them valuable tools in the research process. Firstly, qualitative research instruments allow researchers to gather in-depth and detailed information. Unlike quantitative research instruments that focus on numerical data, qualitative instruments provide rich and descriptive data about participants’ feelings, opinions, and experiences. This depth of information allows researchers to gain a comprehensive understanding of the research topic .

Flexibility and Adaptability in Qualitative Research

Another advantage of qualitative research instruments is their flexibility. Researchers can adapt their methods and questions during data collection to respond to emerging insights. This flexibility allows for a more dynamic and responsive research process, enabling researchers to explore new avenues and uncover unexpected findings.

Capturing Data in Natural Settings

Qualitative research instruments also offer the advantage of capturing data in natural settings. Unlike controlled laboratory settings often used in quantitative research, qualitative research takes place in real-world contexts. This natural setting allows researchers to observe participants’ behaviors and interactions in their natural environment, providing a more authentic and realistic representation of their experiences.

Promoting Participant Engagement and Collaboration

Furthermore, qualitative research instruments promote participant engagement and collaboration. By using methods such as interviews and focus groups, researchers can actively involve participants in the research process. This engagement fosters a sense of ownership and empowerment among participants, leading to more meaningful and insightful data.

Exploring Complex Issues Through Qualitative Research

Lastly, qualitative research instruments allow for the exploration of complex issues. Qualitative research is particularly useful when studying complex phenomena that cannot be easily quantified or measured. It allows researchers to delve into the underlying meanings, motivations, and social dynamics that shape individuals’ behaviors and experiences.

Limitations of Qualitative Research Instruments

Qualitative research instruments have several limitations that researchers need to consider when conducting their studies. In this section, we will delve into the limitations of qualitative research instruments as compared to quantitative research.

Time-Consuming Nature of Qualitative Research

One of the main drawbacks of qualitative research is that the process is time-consuming. Unlike quantitative research, which can collect data from a large sample size in a relatively short period of time, qualitative research requires in-depth interviews, observations, and analysis, which can take a significant amount of time.

Subjectivity and Potential Bias in Qualitative Research

Another limitation of qualitative research instruments is that the interpretations are subjective. Since qualitative research focuses on understanding the meaning and context of phenomena, the interpretations of the data can vary depending on the researcher’s perspective and biases. This subjectivity can introduce potential bias and affect the reliability and validity of the findings.

Complexity of Data Analysis

Additionally, qualitative research instruments often involve complex data analysis. Unlike quantitative research, which can use statistical methods to analyze data, qualitative research requires researchers to analyze textual or visual data, which can be time-consuming and challenging. The analysis process involves coding, categorizing, and interpreting the data, which requires expertise and careful attention to detail.

Challenges in Maintaining Anonymity and Privacy

Furthermore, qualitative research instruments may face challenges in maintaining anonymity. In some cases, researchers may need to collect sensitive or personal information from participants, which can raise ethical concerns . Ensuring the privacy and confidentiality of participants’ data can be challenging, and researchers need to take appropriate measures to protect the participants’ identities and maintain their trust.

Limited Generalizability of Qualitative Research Findings

Another limitation of qualitative research instruments is the limited generalizability of the findings. Qualitative research often focuses on a specific context or a small sample size, which may limit the generalizability of the findings to a larger population. While qualitative research provides rich and detailed insights into a particular phenomenon, it may not be representative of the broader population or applicable to other settings.

Difficulty in Replicating Qualitative Research Findings

Lastly, replicating findings in qualitative research can be difficult. Since qualitative research often involves in-depth exploration of a specific phenomenon, replicating the exact conditions and context of the original study can be challenging. This can make it difficult for other researchers to validate or replicate the findings, which is an essential aspect of scientific research.

Despite these limitations, qualitative research instruments offer valuable insights and understanding of complex phenomena. By acknowledging and addressing these limitations, researchers can enhance the rigor and validity of their qualitative research studies.

In conclusion, qualitative research instruments are powerful tools that enable researchers to explore and uncover the complexities of human experiences. By utilizing a range of instruments and considering their advantages and limitations, researchers can enhance the rigor and depth of their qualitative research studies.

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List of Famous Instrument Makers

List of famous instrument makers, with photos, bios, and other information when available. Who are the top instrument makers in the world? This includes the most prominent instrument makers, living and dead, both in America and abroad. This list of notable instrument makers is ordered by their level of prominence, and can be sorted for various bits of information, such as where these historic instrument makers were born and what their nationality is. The people on this list are from different countries, but what they all have in common is that they're all renowned instrument makers.

Items include everything from Bartolomeo Cristofori to Giovanni Battista Guadagnini.

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Bartolomeo Cristofori

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• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Research Question Generator: Best Tool for Students

Stuck formulating a research question? Try the tool we’ve made! With our research question generator, you’ll get a list of ideas for an academic assignment of any level. All you need to do is add the keywords you’re interested in, push the button, and enjoy the result!

Now, here comes your inspiration 😃

Please try again with some different keywords.

Why Use Research Question Generator?

The choice of research topic is a vital step in the process of any academic task completion. Whether you’re working on a small essay or a large dissertation, your topic will make it fail or fly. The best way to cope with the naming task and proceed to the writing part is to use our free online tool for title generation. Its benefits are indisputable.

• The tool generates research questions, not just topics
• It makes questions focused on your field of interest
• It’s free and quick in use

Research Question Generator: How to Use

Using our research question generator tool, you won’t need to crack your brains over this part of the writing assignment anymore. All you need to do is:

• Insert your study topic of interest in the relevant tab
• Choose a subject and click “Generate topics”
• Grab one of the offered options on the list

The results will be preliminary; you should use them as an initial reference point and refine them further for a workable, correctly formulated research question.

Research Questions: Types & Examples

Depending on your type of study (quantitative vs. qualitative), you might need to formulate different research question types. For instance, a typical quantitative research project would need a quantitative research question, which can be created with the following formula:

Variable(s) + object that possesses that variable + socio-demographic characteristics

You can choose among three quantitative research question types: descriptive, comparative, and relationship-based. Let's consider each type in more detail to clarify the practical side of question formulation.

Descriptive

As its name suggests, a descriptive research question inquires about the number, frequency, or intensity of something and aims to describe a quantitative issue. Some examples include:

• How often do people download personal finance apps in 2022?
• How regularly do Americans go on holidays abroad?
• How many subscriptions for paid learning resources do UK students make a year?

Comparative

Comparative research questions presuppose comparing and contrasting things within a research study. You should pick two or more objects, select a criterion for comparison, and discuss it in detail. Here are good examples:

• What is the difference in calorie intake between Japanese and American preschoolers?
• Does male and female social media use duration per day differ in the USA?
• What are the attitudes of Baby Boomers versus Millennials to freelance work?

Relationship-based

Relationship-based research is a bit more complex, so you'll need extra work to formulate a good research question. Here, you should single out:

• The independent variable
• The dependent variable
• The socio-demographics of your population of interest

Let’s illustrate how it works:

• How does the socio-economic status affect schoolchildren’s dropout rates in the UK?
• What is the relationship between screen time and obesity among American preschoolers?

Research Question Maker FAQ

In a nutshell, a research question is the one you set to answer by performing a specific academic study. Thus, for instance, if your research question is, “How did global warming affect bird migration in California?," you will study bird migration patterns concerning global warming dynamics.

You should think about the population affected by your topic, the specific aspect of your concern, and the timing/historical period you want to study. It’s also necessary to specify the location – a specific country, company, industry sector, the whole world, etc.

A great, effective research question should answer the "who, what, when, where" questions. In other words, you should define the subject of interest, the issue of your concern related to that subject, the timeframe, and the location of your study.

If you don’t know how to write a compelling research question, use our automated tool to complete the task in seconds. You only need to insert your subject of interest, and smart algorithms will do the rest, presenting a set of workable, interesting question suggestions.

Musical Instrument Research Catalog

The Musical Instrument Research Catalog (MIRCat) is a not-for-profit organization that exists to seek and administer funds in support of selected free online digital archives and databases serving researchers, collectors, makers, and caretakers of historical musical instruments and to foster the continual growth and improvement of those digital resources.

MIRCat offers a select group of non-profit digital research initiatives by funding their technology expenses. This covers the cost of internet service providers and web development expertise for creating practical and intuitive online databases and other resources. Current client initiatives at various levels of development include the following:

Clementi grand piano, Duke U. Coll. of Musical Instruments

Early Pianos Online

An interactive database of  historic pianos (up to 1860) and their makers. Includes instrument details, photographs, and maker biographies. Click to enter.

Taskin Harpsichord, Musical Instrument Museum, Edinburgh

Boalch-Mould Online 

An interactive database of historic harpsichords and clavichords and their makers. Includes maker biographies, details of surviving instruments, and photographs. Click to enter.

Trophy from 1761 Kirkman harpsichord, Sigal Music Museum

MIRCAT Digital Archive 

An online digital archive of information about musical instrument making, restoration, conservation, and care to foster future research. 

Wind Instrument Makers Database

An interactive online edition of the standard index of historical wind instrument makers. This project is in development, with public access planned for 2024.

Historic Trombone Database

Based on information gathered from museums and private collections across the globe, this database catalogs trombones made before 1800.

Praetorius,  Syntagma Musicum , 1614-1620

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Hindenburg takes aim at AI server maker Super Micro with short position

(Reuters) -Hindenburg Research on Tuesday disclosed a short position in Super Micro Computer (NASDAQ: SMCI ) and alleged "accounting manipulation" at the AI server maker, the latest by the short seller whose reports have rocked several high-profile companies.

The report pits the short seller, which has tussled with billionaire-investor Carl Icahn and India's Gautam Adani, against the server marker that has been one of the biggest winners of the generative artificial intelligence boom.

Shares of Super Micro were down 3.5% in morning trade. The stock has nearly doubled in 2024, after more than tripling last year.

Hindenburg said it found evidence of undisclosed related party transactions, failure to abide by export controls, among other issues, citing an investigation that included interviews with former senior employees and litigation records.

"It (Super Micro) benefited as an early mover but still faces significant accounting, governance and compliance issues and offers an inferior product and service now being eroded away by more credible competition," Hindenburg said in its report.

Super Micro did not immediately respond to a request for comment. Reuters could not independently verify the claims in the Hindenburg report.

Close ties with chip giant Nvidia (NASDAQ: NVDA ) have allowed Super Micro, known for its liquid cooling technology for high-power semiconductors, to capitalize on the surge in demand for AI servers.

Though revenue has surged, margins have taken a hit recently due to the rising costs of server production and pricing pressure from rivals including Dell (NYSE: DELL ).

Analysts have flagged the company's hefty spending on supporting new generation of AI chips, including those sold by Nvidia.

The company's shares have also come under pressure in recent months on rising worries that Big Tech could scale back AI spending due to slow payoffs from the billions of dollars they are investing in the technology.

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Department of Molecular Biology

Biochemistry, Biophysics & Structural Biology

Biochemistry and Biophysics are the foundation of all cellular processes and systems. Biochemical processes account for the functions of cellular building blocks, from nucleic acids and proteins to lipids and metabolites, and the formation of complex networks that make a cell or system work. Biophysics explains the complexity of life with the simplicity of physical laws and math.

The mission of our collaborative unit ‘Biochemistry & Biophysics’ is to train the next generation of scientists and to uncover how life works at the molecular level. Our scientists study macromolecular complexes and their specificity, protein design and evolution, and molecular networks. We illuminate how the cytoskeleton determines cell shape, how cells transduce signals, how membranes fuse, how chromatin organizes the genome, how metabolism is coordinated, how viruses hijack cells, how the immune response works, and how cells form patterns and communicate with each other.

We are experts in bioengineering, structural biology, computation and modeling, optics and microscopy, and microfluidics. Some examples of the approaches being used, and in some cases developed, at Princeton include X-ray crystallography, electron microscopy, mass spectrometry, NMR spectroscopy, super-resolution optical microscopy, single-molecule methods, and computational modeling. These tools are being applied to biological problems ranging from protein folding and design, to signal transduction, to intracellular trafficking.

A long-standing tradition and strength of our University is that biologists, chemists and physicists work closely together in an interdisciplinary setting. It is also common to see computational biologists working together with wet-lab biologists to address problems that neither could tackle alone with spectacular results. This is facilitated by the intimate connection between the Department of Molecular Biology with the Departments of Chemistry , Physics and Chemical and Biological Engineering , as well at the Lewis-Sigler Institute for Integrative Genomics

Associated Faculty