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There are, however, many other types of research, often used only in certain narrow fields of research. Further complicating things, many of the types overlap, go by different names depending on the subject area, or are differentiated only by very subtle differences. For more detailed explanations of the types of research commonly used in your field, please consult references related to research in your specific subject area.
Because secondary research is so widely used, even by non-researchers, and because its practice is relatively consistent between disciplines, we will cover it in more detail on other pages of this guide.
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- Next: Secondary Research | Literature Review >>
- Last Updated: May 21, 2024 9:38 AM
- URL: https://guides.library.iit.edu/research_basics
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Methodology
- What Is Qualitative Research? | Methods & Examples
What Is Qualitative Research? | Methods & Examples
Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.
Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.
Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.
Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.
- How does social media shape body image in teenagers?
- How do children and adults interpret healthy eating in the UK?
- What factors influence employee retention in a large organization?
- How is anxiety experienced around the world?
- How can teachers integrate social issues into science curriculums?
Table of contents
Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.
Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.
Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.
Qualitative research approaches Approach | What does it involve? |
Grounded theory | Researchers collect rich data on a topic of interest and develop theories . |
| Researchers immerse themselves in groups or organizations to understand their cultures. |
Action research | Researchers and participants collaboratively link theory to practice to drive social change. |
Phenomenological research | Researchers investigate a phenomenon or event by describing and interpreting participants’ lived experiences. |
Narrative research | Researchers examine how stories are told to understand how participants perceive and make sense of their experiences. |
Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.
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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:
- Observations: recording what you have seen, heard, or encountered in detailed field notes.
- Interviews: personally asking people questions in one-on-one conversations.
- Focus groups: asking questions and generating discussion among a group of people.
- Surveys : distributing questionnaires with open-ended questions.
- Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
- You take field notes with observations and reflect on your own experiences of the company culture.
- You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
- You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.
Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.
For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.
Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.
Most types of qualitative data analysis share the same five steps:
- Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
- Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
- Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
- Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
- Identify recurring themes. Link codes together into cohesive, overarching themes.
There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.
Qualitative data analysis Approach | When to use | Example |
| To describe and categorize common words, phrases, and ideas in qualitative data. | A market researcher could perform content analysis to find out what kind of language is used in descriptions of therapeutic apps. |
| To identify and interpret patterns and themes in qualitative data. | A psychologist could apply thematic analysis to travel blogs to explore how tourism shapes self-identity. |
| To examine the content, structure, and design of texts. | A media researcher could use textual analysis to understand how news coverage of celebrities has changed in the past decade. |
| To study communication and how language is used to achieve effects in specific contexts. | A political scientist could use discourse analysis to study how politicians generate trust in election campaigns. |
Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:
The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.
Data collection occurs in real-world contexts or in naturalistic ways.
Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.
Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.
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Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:
The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.
Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.
Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .
Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.
If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.
- Chi square goodness of fit test
- Degrees of freedom
- Null hypothesis
- Discourse analysis
- Control groups
- Mixed methods research
- Non-probability sampling
- Quantitative research
- Inclusion and exclusion criteria
Research bias
- Rosenthal effect
- Implicit bias
- Cognitive bias
- Selection bias
- Negativity bias
- Status quo bias
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.
There are five common approaches to qualitative research :
- Grounded theory involves collecting data in order to develop new theories.
- Ethnography involves immersing yourself in a group or organization to understand its culture.
- Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
- Phenomenological research involves investigating phenomena through people’s lived experiences.
- Action research links theory and practice in several cycles to drive innovative changes.
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.
There are various approaches to qualitative data analysis , but they all share five steps in common:
- Prepare and organize your data.
- Review and explore your data.
- Develop a data coding system.
- Assign codes to the data.
- Identify recurring themes.
The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .
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Home » Scientific Research – Types, Purpose and Guide
Scientific Research – Types, Purpose and Guide
Table of Contents
Scientific Research
Definition:
Scientific research is the systematic and empirical investigation of phenomena, theories, or hypotheses, using various methods and techniques in order to acquire new knowledge or to validate existing knowledge.
It involves the collection, analysis, interpretation, and presentation of data, as well as the formulation and testing of hypotheses. Scientific research can be conducted in various fields, such as natural sciences, social sciences, and engineering, and may involve experiments, observations, surveys, or other forms of data collection. The goal of scientific research is to advance knowledge, improve understanding, and contribute to the development of solutions to practical problems.
Types of Scientific Research
There are different types of scientific research, which can be classified based on their purpose, method, and application. In this response, we will discuss the four main types of scientific research.
Descriptive Research
Descriptive research aims to describe or document a particular phenomenon or situation, without altering it in any way. This type of research is usually done through observation, surveys, or case studies. Descriptive research is useful in generating ideas, understanding complex phenomena, and providing a foundation for future research. However, it does not provide explanations or causal relationships between variables.
Exploratory Research
Exploratory research aims to explore a new area of inquiry or develop initial ideas for future research. This type of research is usually conducted through observation, interviews, or focus groups. Exploratory research is useful in generating hypotheses, identifying research questions, and determining the feasibility of a larger study. However, it does not provide conclusive evidence or establish cause-and-effect relationships.
Experimental Research
Experimental research aims to test cause-and-effect relationships between variables by manipulating one variable and observing the effects on another variable. This type of research involves the use of an experimental group, which receives a treatment, and a control group, which does not receive the treatment. Experimental research is useful in establishing causal relationships, replicating results, and controlling extraneous variables. However, it may not be feasible or ethical to manipulate certain variables in some contexts.
Correlational Research
Correlational research aims to examine the relationship between two or more variables without manipulating them. This type of research involves the use of statistical techniques to determine the strength and direction of the relationship between variables. Correlational research is useful in identifying patterns, predicting outcomes, and testing theories. However, it does not establish causation or control for confounding variables.
Scientific Research Methods
Scientific research methods are used in scientific research to investigate phenomena, acquire knowledge, and answer questions using empirical evidence. Here are some commonly used scientific research methods:
Observational Studies
This method involves observing and recording phenomena as they occur in their natural setting. It can be done through direct observation or by using tools such as cameras, microscopes, or sensors.
Experimental Studies
This method involves manipulating one or more variables to determine the effect on the outcome. This type of study is often used to establish cause-and-effect relationships.
Survey Research
This method involves collecting data from a large number of people by asking them a set of standardized questions. Surveys can be conducted in person, over the phone, or online.
Case Studies
This method involves in-depth analysis of a single individual, group, or organization. Case studies are often used to gain insights into complex or unusual phenomena.
Meta-analysis
This method involves combining data from multiple studies to arrive at a more reliable conclusion. This technique can be used to identify patterns and trends across a large number of studies.
Qualitative Research
This method involves collecting and analyzing non-numerical data, such as interviews, focus groups, or observations. This type of research is often used to explore complex phenomena and to gain an understanding of people’s experiences and perspectives.
Quantitative Research
This method involves collecting and analyzing numerical data using statistical techniques. This type of research is often used to test hypotheses and to establish cause-and-effect relationships.
Longitudinal Studies
This method involves following a group of individuals over a period of time to observe changes and to identify patterns and trends. This type of study can be used to investigate the long-term effects of a particular intervention or exposure.
Data Analysis Methods
There are many different data analysis methods used in scientific research, and the choice of method depends on the type of data being collected and the research question. Here are some commonly used data analysis methods:
- Descriptive statistics: This involves using summary statistics such as mean, median, mode, standard deviation, and range to describe the basic features of the data.
- Inferential statistics: This involves using statistical tests to make inferences about a population based on a sample of data. Examples of inferential statistics include t-tests, ANOVA, and regression analysis.
- Qualitative analysis: This involves analyzing non-numerical data such as interviews, focus groups, and observations. Qualitative analysis may involve identifying themes, patterns, or categories in the data.
- Content analysis: This involves analyzing the content of written or visual materials such as articles, speeches, or images. Content analysis may involve identifying themes, patterns, or categories in the content.
- Data mining: This involves using automated methods to analyze large datasets to identify patterns, trends, or relationships in the data.
- Machine learning: This involves using algorithms to analyze data and make predictions or classifications based on the patterns identified in the data.
Application of Scientific Research
Scientific research has numerous applications in many fields, including:
- Medicine and healthcare: Scientific research is used to develop new drugs, medical treatments, and vaccines. It is also used to understand the causes and risk factors of diseases, as well as to develop new diagnostic tools and medical devices.
- Agriculture : Scientific research is used to develop new crop varieties, to improve crop yields, and to develop more sustainable farming practices.
- Technology and engineering : Scientific research is used to develop new technologies and engineering solutions, such as renewable energy systems, new materials, and advanced manufacturing techniques.
- Environmental science : Scientific research is used to understand the impacts of human activity on the environment and to develop solutions for mitigating those impacts. It is also used to monitor and manage natural resources, such as water and air quality.
- Education : Scientific research is used to develop new teaching methods and educational materials, as well as to understand how people learn and develop.
- Business and economics: Scientific research is used to understand consumer behavior, to develop new products and services, and to analyze economic trends and policies.
- Social sciences : Scientific research is used to understand human behavior, attitudes, and social dynamics. It is also used to develop interventions to improve social welfare and to inform public policy.
How to Conduct Scientific Research
Conducting scientific research involves several steps, including:
- Identify a research question: Start by identifying a question or problem that you want to investigate. This question should be clear, specific, and relevant to your field of study.
- Conduct a literature review: Before starting your research, conduct a thorough review of existing research in your field. This will help you identify gaps in knowledge and develop hypotheses or research questions.
- Develop a research plan: Once you have a research question, develop a plan for how you will collect and analyze data to answer that question. This plan should include a detailed methodology, a timeline, and a budget.
- Collect data: Depending on your research question and methodology, you may collect data through surveys, experiments, observations, or other methods.
- Analyze data: Once you have collected your data, analyze it using appropriate statistical or qualitative methods. This will help you draw conclusions about your research question.
- Interpret results: Based on your analysis, interpret your results and draw conclusions about your research question. Discuss any limitations or implications of your findings.
- Communicate results: Finally, communicate your findings to others in your field through presentations, publications, or other means.
Purpose of Scientific Research
The purpose of scientific research is to systematically investigate phenomena, acquire new knowledge, and advance our understanding of the world around us. Scientific research has several key goals, including:
- Exploring the unknown: Scientific research is often driven by curiosity and the desire to explore uncharted territory. Scientists investigate phenomena that are not well understood, in order to discover new insights and develop new theories.
- Testing hypotheses: Scientific research involves developing hypotheses or research questions, and then testing them through observation and experimentation. This allows scientists to evaluate the validity of their ideas and refine their understanding of the phenomena they are studying.
- Solving problems: Scientific research is often motivated by the desire to solve practical problems or address real-world challenges. For example, researchers may investigate the causes of a disease in order to develop new treatments, or explore ways to make renewable energy more affordable and accessible.
- Advancing knowledge: Scientific research is a collective effort to advance our understanding of the world around us. By building on existing knowledge and developing new insights, scientists contribute to a growing body of knowledge that can be used to inform decision-making, solve problems, and improve our lives.
Examples of Scientific Research
Here are some examples of scientific research that are currently ongoing or have recently been completed:
- Clinical trials for new treatments: Scientific research in the medical field often involves clinical trials to test new treatments for diseases and conditions. For example, clinical trials may be conducted to evaluate the safety and efficacy of new drugs or medical devices.
- Genomics research: Scientists are conducting research to better understand the human genome and its role in health and disease. This includes research on genetic mutations that can cause diseases such as cancer, as well as the development of personalized medicine based on an individual’s genetic makeup.
- Climate change: Scientific research is being conducted to understand the causes and impacts of climate change, as well as to develop solutions for mitigating its effects. This includes research on renewable energy technologies, carbon capture and storage, and sustainable land use practices.
- Neuroscience : Scientists are conducting research to understand the workings of the brain and the nervous system, with the goal of developing new treatments for neurological disorders such as Alzheimer’s disease and Parkinson’s disease.
- Artificial intelligence: Researchers are working to develop new algorithms and technologies to improve the capabilities of artificial intelligence systems. This includes research on machine learning, computer vision, and natural language processing.
- Space exploration: Scientific research is being conducted to explore the cosmos and learn more about the origins of the universe. This includes research on exoplanets, black holes, and the search for extraterrestrial life.
When to use Scientific Research
Some specific situations where scientific research may be particularly useful include:
- Solving problems: Scientific research can be used to investigate practical problems or address real-world challenges. For example, scientists may investigate the causes of a disease in order to develop new treatments, or explore ways to make renewable energy more affordable and accessible.
- Decision-making: Scientific research can provide evidence-based information to inform decision-making. For example, policymakers may use scientific research to evaluate the effectiveness of different policy options or to make decisions about public health and safety.
- Innovation : Scientific research can be used to develop new technologies, products, and processes. For example, research on materials science can lead to the development of new materials with unique properties that can be used in a range of applications.
- Knowledge creation : Scientific research is an important way of generating new knowledge and advancing our understanding of the world around us. This can lead to new theories, insights, and discoveries that can benefit society.
Advantages of Scientific Research
There are many advantages of scientific research, including:
- Improved understanding : Scientific research allows us to gain a deeper understanding of the world around us, from the smallest subatomic particles to the largest celestial bodies.
- Evidence-based decision making: Scientific research provides evidence-based information that can inform decision-making in many fields, from public policy to medicine.
- Technological advancements: Scientific research drives technological advancements in fields such as medicine, engineering, and materials science. These advancements can improve quality of life, increase efficiency, and reduce costs.
- New discoveries: Scientific research can lead to new discoveries and breakthroughs that can advance our knowledge in many fields. These discoveries can lead to new theories, technologies, and products.
- Economic benefits : Scientific research can stimulate economic growth by creating new industries and jobs, and by generating new technologies and products.
- Improved health outcomes: Scientific research can lead to the development of new medical treatments and technologies that can improve health outcomes and quality of life for people around the world.
- Increased innovation: Scientific research encourages innovation by promoting collaboration, creativity, and curiosity. This can lead to new and unexpected discoveries that can benefit society.
Limitations of Scientific Research
Scientific research has some limitations that researchers should be aware of. These limitations can include:
- Research design limitations : The design of a research study can impact the reliability and validity of the results. Poorly designed studies can lead to inaccurate or inconclusive results. Researchers must carefully consider the study design to ensure that it is appropriate for the research question and the population being studied.
- Sample size limitations: The size of the sample being studied can impact the generalizability of the results. Small sample sizes may not be representative of the larger population, and may lead to incorrect conclusions.
- Time and resource limitations: Scientific research can be costly and time-consuming. Researchers may not have the resources necessary to conduct a large-scale study, or may not have sufficient time to complete a study with appropriate controls and analysis.
- Ethical limitations : Certain types of research may raise ethical concerns, such as studies involving human or animal subjects. Ethical concerns may limit the scope of the research that can be conducted, or require additional protocols and procedures to ensure the safety and well-being of participants.
- Limitations of technology: Technology may limit the types of research that can be conducted, or the accuracy of the data collected. For example, certain types of research may require advanced technology that is not yet available, or may be limited by the accuracy of current measurement tools.
- Limitations of existing knowledge: Existing knowledge may limit the types of research that can be conducted. For example, if there is limited knowledge in a particular field, it may be difficult to design a study that can provide meaningful results.
About the author
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Researcher, Academic Writer, Web developer
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Three basic types of research can be identified:
- Experimental - Characterised by random assignment to groups, with full control over extraneous variables, and manipulation of independent variables
- Quasi-experimental - Characterised by the study and comparison of naturally-occurring groups
- Non-experimental - Characterised by study of a single sample, without comparison between groups
For some examples, and to test your knowledge, see the quiz .
External Links
- Types of research (alzheimer-europe.org)
- Research types (heart.org)
- Types of Research within qualitative and quantitative (wisc.edu)
- Survey research and design in psychology
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Home Market Research
What is Research: Definition, Methods, Types & Examples
The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.
Content Index
What is Research?
What are the characteristics of research.
- Comparative analysis chart
Qualitative methods
Quantitative methods, 8 tips for conducting accurate research.
Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”
Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .
Research is conducted with a purpose to:
- Identify potential and new customers
- Understand existing customers
- Set pragmatic goals
- Develop productive market strategies
- Address business challenges
- Put together a business expansion plan
- Identify new business opportunities
- Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
- The analysis is based on logical reasoning and involves both inductive and deductive methods.
- Real-time data and knowledge is derived from actual observations in natural settings.
- There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
- It creates a path for generating new questions. Existing data helps create more research opportunities.
- It is analytical and uses all the available data so that there is no ambiguity in inference.
- Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.
What is the purpose of research?
There are three main purposes:
- Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.
LEARN ABOUT: Descriptive Analysis
- Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.
LEARN ABOUT: Best Data Collection Tools
- Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.
Here is a comparative analysis chart for a better understanding:
| | | |
Approach used | Unstructured | Structured | Highly structured |
Conducted through | Asking questions | Asking questions | By using hypotheses. |
Time | Early stages of decision making | Later stages of decision making | Later stages of decision making |
It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.
When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.
To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .
Types of research methods and Examples
Research methods are broadly classified as Qualitative and Quantitative .
Both methods have distinctive properties and data collection methods .
Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.
Types of qualitative methods include:
- One-to-one Interview
- Focus Groups
- Ethnographic studies
- Text Analysis
Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.
Types of quantitative methods include:
- Survey research
- Descriptive research
- Correlational research
LEARN MORE: Descriptive Research vs Correlational Research
Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.
It is essential to ensure that your data is:
- Valid – founded, logical, rigorous, and impartial.
- Accurate – free of errors and including required details.
- Reliable – other people who investigate in the same way can produce similar results.
- Timely – current and collected within an appropriate time frame.
- Complete – includes all the data you need to support your business decisions.
Gather insights
- Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
- Keep track of the frequency with which each of the main findings appears.
- Make a list of your findings from the most common to the least common.
- Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
- Prepare conclusions and recommendations about your study.
- Act on your strategies
- Look for gaps in the information, and consider doing additional inquiry if necessary
- Plan to review the results and consider efficient methods to analyze and interpret results.
Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.
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When Is Wikipedia Useful?
- Can be a useful place to start when you don't know much about a topic. It can be great for background information, but for the type of academic research you will be doing at UMGC, it is better to use an academic subject encyclopedia from one of the library’s databases already mentioned (Gale, SAGE, or Oxford Reference).
- Can be written and edited by anyone . However, unlike the library’s subject encyclopedias, this means the content is dynamic, and can change at any time, and there is no way to guarantee the author’s expertise.
Wikipedia can be safely used in the following ways:
- As a Starting Point - Wikipedia can give you background information on a topic, as well as perspectives you can use when formulating a research topic. You should not cite Wikipedia as a source for your research. You should always validate anything you use for research in a reliable source.
- Finding Sources - The reference list at the bottom of a Wikipedia page allows you to access many types of sources on the topic, including academic journal articles, news sources, and even primary sources. Even if there are no actual links to these sources, you can search the library databases, or Google for full-text copies of articles or books listed.
For more information on contributing to Wikipedia, see Editing and Contributing to Wikipedia , from Cornell University.
For more information on Wikipedia inaccuracies, see: List of Wikipedia controversies
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- Last Updated: Jun 7, 2024 11:53 PM
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What is cloud computing?
With cloud computing, organizations essentially buy a range of services offered by cloud service providers (CSPs). The CSP’s servers host all the client’s applications. Organizations can enhance their computing power more quickly and cheaply via the cloud than by purchasing, installing, and maintaining their own servers.
The cloud-computing model is helping organizations to scale new digital solutions with greater speed and agility—and to create value more quickly. Developers use cloud services to build and run custom applications and to maintain infrastructure and networks for companies of virtually all sizes—especially large global ones. CSPs offer services, such as analytics, to handle and manipulate vast amounts of data. Time to market accelerates, speeding innovation to deliver better products and services across the world.
What are examples of cloud computing’s uses?
Get to know and directly engage with senior mckinsey experts on cloud computing.
Brant Carson is a senior partner in McKinsey’s Vancouver office; Chandra Gnanasambandam and Anand Swaminathan are senior partners in the Bay Area office; William Forrest is a senior partner in the Chicago office; Leandro Santos is a senior partner in the Atlanta office; Kate Smaje is a senior partner in the London office.
Cloud computing came on the scene well before the global pandemic hit, in 2020, but the ensuing digital dash helped demonstrate its power and utility. Here are some examples of how businesses and other organizations employ the cloud:
- A fast-casual restaurant chain’s online orders multiplied exponentially during the 2020 pandemic lockdowns, climbing to 400,000 a day, from 50,000. One pleasant surprise? The company’s online-ordering system could handle the volume—because it had already migrated to the cloud . Thanks to this success, the organization’s leadership decided to accelerate its five-year migration plan to less than one year.
- A biotech company harnessed cloud computing to deliver the first clinical batch of a COVID-19 vaccine candidate for Phase I trials in just 42 days—thanks in part to breakthrough innovations using scalable cloud data storage and computing to facilitate processes ensuring the drug’s safety and efficacy.
- Banks use the cloud for several aspects of customer-service management. They automate transaction calls using voice recognition algorithms and cognitive agents (AI-based online self-service assistants directing customers to helpful information or to a human representative when necessary). In fraud and debt analytics, cloud solutions enhance the predictive power of traditional early-warning systems. To reduce churn, they encourage customer loyalty through holistic retention programs managed entirely in the cloud.
- Automakers are also along for the cloud ride . One company uses a common cloud platform that serves 124 plants, 500 warehouses, and 1,500 suppliers to consolidate real-time data from machines and systems and to track logistics and offer insights on shop floor processes. Use of the cloud could shave 30 percent off factory costs by 2025—and spark innovation at the same time.
That’s not to mention experiences we all take for granted: using apps on a smartphone, streaming shows and movies, participating in videoconferences. All of these things can happen in the cloud.
Learn more about our Cloud by McKinsey , Digital McKinsey , and Technology, Media, & Telecommunications practices.
How has cloud computing evolved?
Going back a few years, legacy infrastructure dominated IT-hosting budgets. Enterprises planned to move a mere 45 percent of their IT-hosting expenditures to the cloud by 2021. Enter COVID-19, and 65 percent of the decision makers surveyed by McKinsey increased their cloud budgets . An additional 55 percent ended up moving more workloads than initially planned. Having witnessed the cloud’s benefits firsthand, 40 percent of companies expect to pick up the pace of implementation.
The cloud revolution has actually been going on for years—more than 20, if you think the takeoff point was the founding of Salesforce, widely seen as the first software as a service (SaaS) company. Today, the next generation of cloud, including capabilities such as serverless computing, makes it easier for software developers to tweak software functions independently, accelerating the pace of release, and to do so more efficiently. Businesses can therefore serve customers and launch products in a more agile fashion. And the cloud continues to evolve.
Introducing McKinsey Explainers : Direct answers to complex questions
Cost savings are commonly seen as the primary reason for moving to the cloud but managing those costs requires a different and more dynamic approach focused on OpEx rather than CapEx. Financial-operations (or FinOps) capabilities can indeed enable the continuous management and optimization of cloud costs . But CSPs have developed their offerings so that the cloud’s greatest value opportunity is primarily through business innovation and optimization. In 2020, the top-three CSPs reached $100 billion in combined revenues—a minor share of the global $2.4 trillion market for enterprise IT services—leaving huge value to be captured. To go beyond merely realizing cost savings, companies must activate three symbiotic rings of cloud value creation : strategy and management, business domain adoption, and foundational capabilities.
What’s the main reason to move to the cloud?
The pandemic demonstrated that the digital transformation can no longer be delayed—and can happen much more quickly than previously imagined. Nothing is more critical to a corporate digital transformation than becoming a cloud-first business. The benefits are faster time to market, simplified innovation and scalability, and reduced risk when effectively managed. The cloud lets companies provide customers with novel digital experiences—in days, not months—and delivers analytics absent on legacy platforms. But to transition to a cloud-first operating model, organizations must make a collective effort that starts at the top. Here are three actions CEOs can take to increase the value their companies get from cloud computing :
- Establish a sustainable funding model.
- Develop a new business technology operating model.
- Set up policies to attract and retain the right engineering talent.
How much value will the cloud create?
Fortune 500 companies adopting the cloud could realize more than $1 trillion in value by 2030, and not from IT cost reductions alone, according to McKinsey’s analysis of 700 use cases.
For example, the cloud speeds up design, build, and ramp-up, shortening time to market when companies have strong DevOps (the combination of development and operations) processes in place; groups of software developers customize and deploy software for operations that support the business. The cloud’s global infrastructure lets companies scale products almost instantly to reach new customers, geographies, and channels. Finally, digital-first companies use the cloud to adopt emerging technologies and innovate aggressively, using digital capabilities as a competitive differentiator to launch and build businesses .
If companies pursue the cloud’s vast potential in the right ways, they will realize huge value. Companies across diverse industries have implemented the public cloud and seen promising results. The successful ones defined a value-oriented strategy across IT and the business, acquired hands-on experience operating in the cloud, adopted a technology-first approach, and developed a cloud-literate workforce.
Learn more about our Cloud by McKinsey and Digital McKinsey practices.
What is the cloud cost/procurement model?
Some cloud services, such as server space, are leased. Leasing requires much less capital up front than buying, offers greater flexibility to switch and expand the use of services, cuts the basic cost of buying hardware and software upfront, and reduces the difficulties of upkeep and ownership. Organizations pay only for the infrastructure and computing services that meet their evolving needs. But an outsourcing model is more apt than other analogies: the computing business issues of cloud customers are addressed by third-party providers that deliver innovative computing services on demand to a wide variety of customers, adapt those services to fit specific needs, and work to constantly improve the offering.
What are cloud risks?
The cloud offers huge cost savings and potential for innovation. However, when companies migrate to the cloud, the simple lift-and-shift approach doesn’t reduce costs, so companies must remediate their existing applications to take advantage of cloud services.
For instance, a major financial-services organization wanted to move more than 50 percent of its applications to the public cloud within five years. Its goals were to improve resiliency, time to market, and productivity. But not all its business units needed to transition at the same pace. The IT leadership therefore defined varying adoption archetypes to meet each unit’s technical, risk, and operating-model needs.
Legacy cybersecurity architectures and operating models can also pose problems when companies shift to the cloud. The resulting problems, however, involve misconfigurations rather than inherent cloud security vulnerabilities. One powerful solution? Securing cloud workloads for speed and agility : automated security architectures and processes enable workloads to be processed at a much faster tempo.
What kind of cloud talent is needed?
The talent demands of the cloud differ from those of legacy IT. While cloud computing can improve the productivity of your technology, it requires specialized and sometimes hard-to-find talent—including full-stack developers, data engineers, cloud-security engineers, identity- and access-management specialists, and cloud engineers. The cloud talent model should thus be revisited as you move forward.
Six practical actions can help your organization build the cloud talent you need :
- Find engineering talent with broad experience and skills.
- Balance talent maturity levels and the composition of teams.
- Build an extensive and mandatory upskilling program focused on need.
- Build an engineering culture that optimizes the developer experience.
- Consider using partners to accelerate development and assign your best cloud leaders as owners.
- Retain top talent by focusing on what motivates them.
How do different industries use the cloud?
Different industries are expected to see dramatically different benefits from the cloud. High-tech, retail, and healthcare organizations occupy the top end of the value capture continuum. Electronics and semiconductors, consumer-packaged-goods, and media companies make up the middle. Materials, chemicals, and infrastructure organizations cluster at the lower end.
Nevertheless, myriad use cases provide opportunities to unlock value across industries , as the following examples show:
- a retailer enhancing omnichannel fulfillment, using AI to optimize inventory across channels and to provide a seamless customer experience
- a healthcare organization implementing remote heath monitoring to conduct virtual trials and improve adherence
- a high-tech company using chatbots to provide premier-level support combining phone, email, and chat
- an oil and gas company employing automated forecasting to automate supply-and-demand modeling and reduce the need for manual analysis
- a financial-services organization implementing customer call optimization using real-time voice recognition algorithms to direct customers in distress to experienced representatives for retention offers
- a financial-services provider moving applications in customer-facing business domains to the public cloud to penetrate promising markets more quickly and at minimal cost
- a health insurance carrier accelerating the capture of billions of dollars in new revenues by moving systems to the cloud to interact with providers through easier onboarding
The cloud is evolving to meet the industry-specific needs of companies. From 2021 to 2024, public-cloud spending on vertical applications (such as warehouse management in retailing and enterprise risk management in banking) is expected to grow by more than 40 percent annually. Spending on horizontal workloads (such as customer relationship management) is expected to grow by 25 percent. Healthcare and manufacturing organizations, for instance, plan to spend around twice as much on vertical applications as on horizontal ones.
Learn more about our Cloud by McKinsey , Digital McKinsey , Financial Services , Healthcare Systems & Services , Retail , and Technology, Media, & Telecommunications practices.
What are the biggest cloud myths?
Views on cloud computing can be clouded by misconceptions. Here are seven common myths about the cloud —all of which can be debunked:
- The cloud’s value lies primarily in reducing costs.
- Cloud computing costs more than in-house computing.
- On-premises data centers are more secure than the cloud.
- Applications run more slowly in the cloud.
- The cloud eliminates the need for infrastructure.
- The best way to move to the cloud is to focus on applications or data centers.
- You must lift and shift applications as-is or totally refactor them.
How large must my organization be to benefit from the cloud?
Here’s one more huge misconception: the cloud is just for big multinational companies. In fact, cloud can help make small local companies become multinational. A company’s benefits from implementing the cloud are not constrained by its size. In fact, the cloud shifts barrier to entry skill rather than scale, making it possible for a company of any size to compete if it has people with the right skills. With cloud, highly skilled small companies can take on established competitors. To realize the cloud’s immense potential value fully, organizations must take a thoughtful approach, with IT and the businesses working together.
For more in-depth exploration of these topics, see McKinsey’s Cloud Insights collection. Learn more about Cloud by McKinsey —and check out cloud-related job opportunities if you’re interested in working at McKinsey.
Articles referenced include:
- “ Six practical actions for building the cloud talent you need ,” January 19, 2022, Brant Carson , Dorian Gärtner , Keerthi Iyengar, Anand Swaminathan , and Wayne Vest
- “ Cloud-migration opportunity: Business value grows, but missteps abound ,” October 12, 2021, Tara Balakrishnan, Chandra Gnanasambandam , Leandro Santos , and Bhargs Srivathsan
- “ Cloud’s trillion-dollar prize is up for grabs ,” February 26, 2021, Will Forrest , Mark Gu, James Kaplan , Michael Liebow, Raghav Sharma, Kate Smaje , and Steve Van Kuiken
- “ Unlocking value: Four lessons in cloud sourcing and consumption ,” November 2, 2020, Abhi Bhatnagar , Will Forrest , Naufal Khan , and Abdallah Salami
- “ Three actions CEOs can take to get value from cloud computing ,” July 21, 2020, Chhavi Arora , Tanguy Catlin , Will Forrest , James Kaplan , and Lars Vinter
Want to know more about cloud computing?
Related articles.
Cloud’s trillion-dollar prize is up for grabs
The cloud transformation engine
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Diabetes treatment: medications for type 2 diabetes.
Lifestyle choices, including eating a healthy diet, exercising and staying at a healthy weight, are key to managing type 2 diabetes. But you also might need to take medication to keep your blood sugar, also called glucose, at a healthy level. Sometimes one medication is enough. In other cases, taking several medications works better.
The list of medications for type 2 diabetes is long and can be confusing. Take time to learn about these medicines — how they're taken, what they do and what side effects they may cause. That can help you get ready to talk to your health care provider about diabetes treatment choices that are right for you.
Diabetes treatment: Lowering blood sugar
Several classes of type 2 diabetes medicines exist. Each class of medicine works in a different way to lower blood sugar. A medication may work by:
- Causing the pancreas to make and release more insulin.
- Limiting the liver's ability to make and release sugar.
- Blocking the action of enzymes in the intestines that break down carbohydrates, slowing how quickly cells take in carbohydrates.
- Improving cells' sensitivity to insulin.
- Limiting the kidneys' ability to take in sugar, which increases the amount of sugar that leaves the body in urine.
- Slowing how quickly food moves through the stomach.
Each class of medicine has one or more medications. Some of these medications are taken by mouth, while others must be taken as a shot.
Compare diabetes medications
Below is a list of common diabetes medications. Other medications are available too. Ask your health care provider about your choices and the pros and cons of each.
Medications you take by mouth
Meglitinides
Medications
- Repaglinide
- Nateglinide
- Trigger the release of insulin from the pancreas
- Work quickly
Possible side effects
- Blood sugar levels drop too low — a condition called hypoglycemia
- Weight gain
Sulfonylureas
- Glipizide (Glucotrol XL)
- Glimepiride (Amaryl)
- Glyburide (DiaBeta, Glynase)
- Effective in lowering blood sugar
- Blood sugar levels drop too low
- Nausea or vomiting if you drink alcohol
Dipeptidyl-peptidase 4 (DPP-4) inhibitors
- Saxagliptin (Onglyza)
- Sitagliptin (Januvia)
- Linagliptin (Tradjenta)
- Alogliptin (Nesina)
- Cause the release of insulin when blood sugar is rising
- Limit the liver's ability to release glucose
- Don't cause weight gain
- Don't cause blood sugar levels to drop too low when used alone or with metformin
- Upper respiratory tract infection
- Sore throat
- Metformin (Fortamet, Glumetza, others)
- Limit the liver's ability to release sugar
- Improve cells' sensitivity to insulin
- Very effective
- May lead to minor weight loss
- Stomach pain
- Very rarely, the harmful buildup of lactic acid — a condition called lactic acidosis —in people with kidney failure or liver failure
Thiazolidinediones
- Rosiglitazone (Avandia)
- Pioglitazone (Actos)
- Limit the liver's ability to make and release sugar
- May slightly increase high-density lipoprotein (HDL) cholesterol, the "good" cholesterol
- Fluid retention
- Increased risk of broken bones
- Increased risk of heart problems, including heart failure
- Possible increased risk of bladder cancer with pioglitazone
People with liver problems or a history of heart failure shouldn't take this kind of diabetes medicine.
Alpha-glucosidase inhibitors
- Miglitol (Glyset)
- Slow the body's ability to breakdown starches and some sugars
- Don't cause blood sugar levels to drop too low unless you take them with insulin or a sulfonylurea
Sodium-glucose transporter 2 (SGLT2) inhibitors
- Canagliflozin (Invokana)
- Dapagliflozin (Farxiga)
- Empagliflozin (Jardiance)
- Ertugliflozin (Steglatro)
- Limit the kidneys' ability to take in sugar, which increases the amount of sugar that leaves the body in urine
- May lead to weight loss
- May lower blood pressure
- Urinary tract infections
- Yeast infections
Bile acid sequestrants
- Colesevelam (Welchol)
- Lower cholesterol and have a small effect in lowering blood sugar when used with other diabetes medications
- Likely safe for people with liver problems
- Constipation
- Indigestion
- Rise in blood fats called triglycerides
Medications you take as a shot
Amylin mimetics
- Pramlintide (Symlin)
- Help regulate blood sugar
- Slow food moving through the stomach
- Used with insulin shots
- May decrease hunger
- Abdominal pain
Incretin mimetic (GLP-1 receptor agonists)
- Dulaglutide (Trulicity)
- Exenatide (Byetta, Bydureon Bcise)
- Liraglutide (Saxenda, Victoza)
- Lixisenatide (Adlyxin)
- Semaglutide (Ozempic, Rybelsus, Wegovy)
- Cause the release of insulin as blood sugar levels are rising
- May be used with metformin, basal insulin or a sulfonylurea
- Increased risk of inflamed pancreas — a condition called pancreatitis
How to choose your diabetes medication
No one diabetes treatment is best for everyone. What works for one person may not work for another. Your health care provider can explain how one medication or multiple medications may fit into your diabetes treatment plan. Sometimes combining medicines may increase the effectiveness of each individual medicine to lower blood sugar. Talk to your provider about the pros and cons of specific diabetes medications for you.
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- Papadakis MA, et al., eds. Diabetes mellitus and hypoglycemia. In: Current Medical Diagnosis & Treatment 2023. 62nd ed. McGraw-Hill; 2023. https://accessmedicine.mhmedical.com. Accessed Sept. 22, 2022.
- Wexler DJ. Overview of general medical care in nonpregnant adults with diabetes mellitus. https://www.uptodate.com/contents/search. Accessed Sept. 22, 2022.
- Oral medication: What are my options? American Diabetes Association. https://diabetes.org/healthy-living/medication-treatments/oral-medication/what-are-my-options. Accessed Sept. 22, 2022.
- Wexler DJ. Sulfonylureas and meglitinides in the treatment of diabetes mellitus. https://www.uptodate.com/contents/search. Accessed Sept. 22, 2022.
- Melmed S, et al., eds. Therapeutics of type 2 diabetes mellitus. In: Williams Textbook of Endocrinology. 14th ed. Elsevier; 2016. https://www.clinicalkey.com. Accessed Sept. 22, 2022.
- Castro MR (expert opinion). Mayo Clinic. Sept. 22, 2022.
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Types of Research Method 1. Observatory Research Method 2. Correlation Research Method . Non-empirical research. Non-empirical (theoretical) research is an approach that involves the development of theory as opposed to using observation and experimentation. As such, non-empirical research seeks solutions to problems using existing knowledge as ...
Qualitative research is a type of research that aims to gather and analyse non-numerical (descriptive) data in order to gain an understanding of individuals' social reality, including understanding their attitudes, beliefs, and motivation. This type of research typically involves in-depth interviews, focus groups, or observations in order to collect data that is rich in detail and context.
In its most common sense, methodology is the study of research methods. However, the term can also refer to the methods themselves or to the philosophical discussion of associated background assumptions. A method is a structured procedure for bringing about a certain goal, like acquiring knowledge or verifying knowledge claims. This normally involves various steps, like choosing a sample ...
Descriptive research is mainly done when a researcher wants to gain a better understanding of a topic. That is, analysis of the past as opposed to the future. Descriptive research is the exploration of the existing certain phenomena. The details of the facts won't be known. The existing phenomena's facts are not known to the person.
About Research Methods. This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. As Patten and Newhart note in the book Understanding Research Methods, "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge.
Research. Research is a way of looking for new information, new understanding, and new facts. A person who does research is called a researcher. Some researchers work in academia. Other researchers work for businesses, for organisations, or for the government. Research is often used for solving problems or increasing available knowledge.
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.
Types of Research Designs Compared | Guide & Examples. Published on June 20, 2019 by Shona McCombes.Revised on June 22, 2023. When you start planning a research project, developing research questions and creating a research design, you will have to make various decisions about the type of research you want to do.. There are many ways to categorize different types of research.
Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design. When planning your methods, there are two key decisions you will make. First, decide how you will collect data. Your methods depend on what type of data you need to answer your research question:
This type of research is used to measure what impact a specific change will have on existing norms and assumptions. Most social scientists seek causal explanations that reflect tests of hypotheses. ... 2377-2394; Exploratory Research. Wikipedia. Field Research Design. Definition and Purpose. Sometimes referred to as ethnography or participant ...
Qualitative research refers to the meanings, definitions, characteristics, symbols, metaphors, and description of things. Qualitative research is much more subjective and uses very different methods of collecting information, mainly individual, in-depth interviews and focus groups. The nature of this type of research is exploratory and open ended.
Expands human knowledge. Similar to analytical or basic research. Secondary. Consolidates existing knowledge. Establishes what's already known. Proves the need for primary research. Discovers methods and protocols for primary research. Similar to descriptive research. There are, however, many other types of research, often used only in ...
Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research. Qualitative research is the opposite of quantitative research, which involves collecting and ...
Contents. Research is defined as human activity based on intellectual application in the investigation of matter. The primary purpose for applied research is discovering, interpreting, and the development of methods and systems for the advancement of human knowledge on a wide variety of scientific matters of our world and the universe.
Scientific research is the systematic and empirical investigation of phenomena, theories, or hypotheses, using various methods and techniques in order to acquire new knowledge or to validate existing knowledge. It involves the collection, analysis, interpretation, and presentation of data, as well as the formulation and testing of hypotheses.
Research is defined as a meticulous and systematic inquiry process designed to explore and unravel specific subjects or issues with precision. This methodical approach encompasses the thorough collection, rigorous analysis, and insightful interpretation of information, aiming to delve deep into the nuances of a chosen field of study.
Three basic types of research can be identified: Experimental - Characterised by random assignment to groups, with full control over extraneous variables, and manipulation of independent variables. Quasi-experimental - Characterised by the study and comparison of naturally-occurring groups. Non-experimental - Characterised by study of a single ...
Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, "research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.".
Example: A researcher examines if and how employee satisfaction changes in the same employees after one year, three years and five years with the same company. 16. Mixed research. Mixed research includes both qualitative and quantitative data. The results are often presented as a mix of graphs, words and images.
Wikipedia: Can be a useful place to start when you don't know much about a topic. It can be great for background information, but for the type of academic research you will be doing at UMGC, it is better to use an academic subject encyclopedia from one of the library's databases already mentioned (Gale, SAGE, or Oxford Reference).
Cloud computing is the use of comprehensive digital capabilities delivered via the internet for organizations to operate, innovate, and serve customers. It eliminates the need for organizations to host digital applications on their own servers. Group of white spheres on light blue background.
Diarrhea. Sodium-glucose transporter 2 (SGLT2) inhibitors. Medications. Canagliflozin (Invokana) Dapagliflozin (Farxiga) Empagliflozin (Jardiance) Ertugliflozin (Steglatro) Action. Limit the kidneys' ability to take in sugar, which increases the amount of sugar that leaves the body in urine.