» » » » » , An is a hypothesis that there is a relationship between variables. This includes any hypothesis that predicts , , non-directional correlation or . The only that isn't an alternative hypothesis is a that predicts no relationship between independent and dependent variables. The following are hypothetical examples of an alternative hypothesis. Years of kendo experience has a positive correlation with personal resilience. Coffee drinkers have higher average productivity than people who don't drink coffee. Temperature influences the volume of alcohol. Rain causes mud puddles. There is a positive correlation between the price of silver and gold. Beeswax can be used to waterproof shoes. People feel happier on Fridays. People use the internet more on Mondays than any other day of the week. Social media use has a positive correlation with self-reported unhappiness. Smoking has a negative correlation with health. Income has a positive correlation with residential air quality. Room color influences mood. Temperature influences the strength of bamboo. Residential noise pollution has a positive correlation with self-reported stress levels. Low air quality has a negative correlation to health. Bacteria growth is correlated with air temperature. is positively correlated to career advancement and income. The statements above are examples of hypotheses and are therefore statements of fact. Overview: Alternative Hypothesis | | | | | | | | Non-directional Correlation | | | | » » » » » » |
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Hypothesis testing involves the careful construction of two statements: the null hypothesis and the alternative hypothesis. These hypotheses can look very similar but are actually different. How do we know which hypothesis is the null and which one is the alternative? We will see that there are a few ways to tell the difference. The Null HypothesisThe null hypothesis reflects that there will be no observed effect in our experiment. In a mathematical formulation of the null hypothesis, there will typically be an equal sign. This hypothesis is denoted by H 0 . The null hypothesis is what we attempt to find evidence against in our hypothesis test. We hope to obtain a small enough p-value that it is lower than our level of significance alpha and we are justified in rejecting the null hypothesis. If our p-value is greater than alpha, then we fail to reject the null hypothesis. If the null hypothesis is not rejected, then we must be careful to say what this means. The thinking on this is similar to a legal verdict. Just because a person has been declared "not guilty", it does not mean that he is innocent. In the same way, just because we failed to reject a null hypothesis it does not mean that the statement is true. For example, we may want to investigate the claim that despite what convention has told us, the mean adult body temperature is not the accepted value of 98.6 degrees Fahrenheit . The null hypothesis for an experiment to investigate this is “The mean adult body temperature for healthy individuals is 98.6 degrees Fahrenheit.” If we fail to reject the null hypothesis, then our working hypothesis remains that the average adult who is healthy has a temperature of 98.6 degrees. We do not prove that this is true. If we are studying a new treatment, the null hypothesis is that our treatment will not change our subjects in any meaningful way. In other words, the treatment will not produce any effect in our subjects. The Alternative HypothesisThe alternative or experimental hypothesis reflects that there will be an observed effect for our experiment. In a mathematical formulation of the alternative hypothesis, there will typically be an inequality, or not equal to symbol. This hypothesis is denoted by either H a or by H 1 . The alternative hypothesis is what we are attempting to demonstrate in an indirect way by the use of our hypothesis test. If the null hypothesis is rejected, then we accept the alternative hypothesis. If the null hypothesis is not rejected, then we do not accept the alternative hypothesis. Going back to the above example of mean human body temperature, the alternative hypothesis is “The average adult human body temperature is not 98.6 degrees Fahrenheit.” If we are studying a new treatment, then the alternative hypothesis is that our treatment does, in fact, change our subjects in a meaningful and measurable way. The following set of negations may help when you are forming your null and alternative hypotheses. Most technical papers rely on just the first formulation, even though you may see some of the others in a statistics textbook. - Null hypothesis: “ x is equal to y .” Alternative hypothesis “ x is not equal to y .”
- Null hypothesis: “ x is at least y .” Alternative hypothesis “ x is less than y .”
- Null hypothesis: “ x is at most y .” Alternative hypothesis “ x is greater than y .”
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What is an Alternative Hypothesis? Definition, Types, and ExamplesThe alternative hypothesis is a way to propose a contrasting view on a proposed theory by a researcher. It tries to prove the original statement provided by the null statement false. What is an Alternative Hypothesis?An alternative hypothesis is a contradictory theory to that taken by a Null Hypothesis about a specified research parameter. The null hypothesis proposes that there is no relation between the independent and dependent variables in a population parameter. If the null hypothesis is true, then these variables do not change mutually. Understanding Alternative HypothesisSimilarly, hypothesis testing directly compares the observed data in a defined population data set with the Null hypothesis results. Types of Alternative HypothesisThere are two main types of alternative hypotheses. Two-Tailed or Non-Directional Hypothesis Examples of Alternative HypothesisSuppose a high school proposes that providing a laptop to all students during classes will improve their grades among other students in the school. At the same time, the school can propose an alternative hypothesis stating: An investment firm wants to set up an index fund following the S&P500 index. The null hypothesis states an index fund generates a 10% rate of return when followed the same way as S&P500. Null Hypothesis Vs. Alternative Hypothesis – Key DifferencesAn alternative hypothesis assumes the null statement is wrong. It means it discredits the original statements or tries to prove that statement false. Hypothesis Tests Result Interpretations (implication) Similarly, the alternative hypothesis can be right or wrong. Further research can propose another point of view and another alternative theory. Related Posts7 best internal source of fund that company could benefit from (example and explanation), 5 nature and 7 scope of financial management you should know, what is operating gearing definition, formula, example, and usages, what is financial gearing and why is it happening. Know the Differences & Comparisons Difference Between Null and Alternative HypothesisNull hypothesis implies a statement that expects no difference or effect. On the contrary, an alternative hypothesis is one that expects some difference or effect. Null hypothesis This article excerpt shed light on the fundamental differences between null and alternative hypothesis. Content: Null Hypothesis Vs Alternative HypothesisComparison chart. Basis for Comparison | Null Hypothesis | Alternative Hypothesis | Meaning | A null hypothesis is a statement, in which there is no relationship between two variables. | An alternative hypothesis is statement in which there is some statistical significance between two measured phenomenon. | Represents | No observed effect | Some observed effect | What is it? | It is what the researcher tries to disprove. | It is what the researcher tries to prove. | Acceptance | No changes in opinions or actions | Changes in opinions or actions | Testing | Indirect and implicit | Direct and explicit | Observations | Result of chance | Result of real effect | Denoted by | H-zero | H-one | Mathematical formulation | Equal sign | Unequal sign | Definition of Null HypothesisA null hypothesis is a statistical hypothesis in which there is no significant difference exist between the set of variables. It is the original or default statement, with no effect, often represented by H 0 (H-zero). It is always the hypothesis that is tested. It denotes the certain value of population parameter such as µ, s, p. A null hypothesis can be rejected, but it cannot be accepted just on the basis of a single test. Definition of Alternative HypothesisA statistical hypothesis used in hypothesis testing, which states that there is a significant difference between the set of variables. It is often referred to as the hypothesis other than the null hypothesis, often denoted by H 1 (H-one). It is what the researcher seeks to prove in an indirect way, by using the test. It refers to a certain value of sample statistic, e.g., x¯, s, p The acceptance of alternative hypothesis depends on the rejection of the null hypothesis i.e. until and unless null hypothesis is rejected, an alternative hypothesis cannot be accepted. Key Differences Between Null and Alternative HypothesisThe important points of differences between null and alternative hypothesis are explained as under: - A null hypothesis is a statement, in which there is no relationship between two variables. An alternative hypothesis is a statement; that is simply the inverse of the null hypothesis, i.e. there is some statistical significance between two measured phenomenon.
- A null hypothesis is what, the researcher tries to disprove whereas an alternative hypothesis is what the researcher wants to prove.
- A null hypothesis represents, no observed effect whereas an alternative hypothesis reflects, some observed effect.
- If the null hypothesis is accepted, no changes will be made in the opinions or actions. Conversely, if the alternative hypothesis is accepted, it will result in the changes in the opinions or actions.
- As null hypothesis refers to population parameter, the testing is indirect and implicit. On the other hand, the alternative hypothesis indicates sample statistic, wherein, the testing is direct and explicit.
- A null hypothesis is labelled as H 0 (H-zero) while an alternative hypothesis is represented by H 1 (H-one).
- The mathematical formulation of a null hypothesis is an equal sign but for an alternative hypothesis is not equal to sign.
- In null hypothesis, the observations are the outcome of chance whereas, in the case of the alternative hypothesis, the observations are an outcome of real effect.
There are two outcomes of a statistical test, i.e. first, a null hypothesis is rejected and alternative hypothesis is accepted, second, null hypothesis is accepted, on the basis of the evidence. In simple terms, a null hypothesis is just opposite of alternative hypothesis. You Might Also Like:Zipporah Thuo says February 22, 2018 at 6:06 pm The comparisons between the two hypothesis i.e Null hypothesis and the Alternative hypothesis are the best.Thank you. Getu Gamo says March 4, 2019 at 3:42 am Thank you so much for the detail explanation on two hypotheses. Now I understood both very well, including their differences. Jyoti Bhardwaj says May 28, 2019 at 6:26 am Thanks, Surbhi! Appreciate the clarity and precision of this content. January 9, 2020 at 6:16 am John Jenstad says July 20, 2020 at 2:52 am Thanks very much, Surbhi, for your clear explanation!! Navita says July 2, 2021 at 11:48 am Thanks for the Comparison chart! it clears much of my doubt. GURU UPPALA says July 21, 2022 at 8:36 pm Thanks for the Comparison chart! Enock kipkoech says September 22, 2022 at 1:57 pm What are the examples of null hypothesis and substantive hypothesis Leave a Reply Cancel replyYour email address will not be published. Required fields are marked * Save my name, email, and website in this browser for the next time I comment. Alternative HypothesisAlternative hypothesis defines there is a statistically important relationship between two variables. Whereas null hypothesis states there is no statistical relationship between the two variables. In statistics, we usually come across various kinds of hypotheses. A statistical hypothesis is supposed to be a working statement which is assumed to be logical with given data. It should be noticed that a hypothesis is neither considered true nor false. The alternative hypothesis is a statement used in statistical inference experiment. It is contradictory to the null hypothesis and denoted by H a or H 1 . We can also say that it is simply an alternative to the null. In hypothesis testing, an alternative theory is a statement which a researcher is testing. This statement is true from the researcher’s point of view and ultimately proves to reject the null to replace it with an alternative assumption. In this hypothesis, the difference between two or more variables is predicted by the researchers, such that the pattern of data observed in the test is not due to chance. To check the water quality of a river for one year, the researchers are doing the observation. As per the null hypothesis, there is no change in water quality in the first half of the year as compared to the second half. But in the alternative hypothesis, the quality of water is poor in the second half when observed. Difference Between Null and Alternative Hypothesis | | It denotes there is no relationship between two measured phenomena. | It’s a hypothesis that a random cause may influence the observed data or sample. | It is represented by H | It is represented by H or H | Example: Rohan will win at least Rs.100000 in lucky draw. | Example: Rohan will win less than Rs.100000 in lucky draw. | Basically, there are three types of the alternative hypothesis, they are; Left-Tailed : Here, it is expected that the sample proportion (π) is less than a specified value which is denoted by π 0 , such that; H 1 : π < π 0 Right-Tailed: It represents that the sample proportion (π) is greater than some value, denoted by π 0 . H 1 : π > π 0 Two-Tailed: According to this hypothesis, the sample proportion (denoted by π) is not equal to a specific value which is represented by π 0 . H 1 : π ≠ π 0 Note: The null hypothesis for all the three alternative hypotheses, would be H 1 : π = π 0 . Register with BYJU'S & Download Free PDFsRegister with byju's & watch live videos. - school Campus Bookshelves
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selected template will load here This action is not available. 8.4: The Alternative Hypothesis- Last updated
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- Page ID 14493
- Foster et al.
- University of Missouri-St. Louis, Rice University, & University of Houston, Downtown Campus via University of Missouri’s Affordable and Open Access Educational Resources Initiative
\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \) \( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) ( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\) \( \newcommand{\vectorA}[1]{\vec{#1}} % arrow\) \( \newcommand{\vectorAt}[1]{\vec{\text{#1}}} % arrow\) \( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vectorC}[1]{\textbf{#1}} \) \( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \) \( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \) \( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \) If the null hypothesis is rejected, then we will need some other explanation, which we call the alternative hypothesis, \(H_A\) or \(H_1\). The alternative hypothesis is simply the reverse of the null hypothesis, and there are three options, depending on where we expect the difference to lie. Thus, our alternative hypothesis is the mathematical way of stating our research question. If we expect our obtained sample mean to be above or below the null hypothesis value, which we call a directional hypothesis, then our alternative hypothesis takes the form: \[\mathrm{H}_{\mathrm{A}}: \mu>7.47 \quad \text { or } \quad \mathrm{H}_{\mathrm{A}}: \mu<7.47 \nonumber \] based on the research question itself. We should only use a directional hypothesis if we have good reason, based on prior observations or research, to suspect a particular direction. When we do not know the direction, such as when we are entering a new area of research, we use a non-directional alternative: \[\mathrm{H}_{\mathrm{A}}: \mu \neq 7.47 \nonumber \] We will set different criteria for rejecting the null hypothesis based on the directionality (greater than, less than, or not equal to) of the alternative. To understand why, we need to see where our criteria come from and how they relate to \(z\)-scores and distributions. Writing hypotheses in words As we alluded to in the null hypothesis section, we can write our hypotheses in word statements (in addition to the statements with symbols). These statements should be specific enough to the particular experiment or situation being referred to. That is, don't make them generic enough so that they would apply to any hypothesis test that you would conduct. Examples for how to write null and alternate hypotheses in words for directional and non-directional situations are given throughout the chapters. Contributors and AttributionsFoster et al. (University of Missouri-St. Louis, Rice University, & University of Houston, Downtown Campus) - School Guide
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Alternative Hypothesis: Definition, Types and ExamplesIn statistical hypothesis testing, the alternative hypothesis is an important proposition in the hypothesis test. The goal of the hypothesis test is to demonstrate that in the given condition, there is sufficient evidence supporting the credibility of the alternative hypothesis instead of the default assumption made by the null hypothesis. Alternative Hypotheses Both hypotheses include statements with the same purpose of providing the researcher with a basic guideline. The researcher uses the statement from each hypothesis to guide their research. In statistics, alternative hypothesis is often denoted as H a or H 1 . Table of Content What is a Hypothesis?Alternative hypothesis, types of alternative hypothesis, difference between null and alternative hypothesis, formulating an alternative hypothesis, example of alternative hypothesis, application of alternative hypothesis. “A hypothesis is a statement of a relationship between two or more variables.” It is a working statement or theory that is based on insufficient evidence. While experimenting, researchers often make a claim, that they can test. These claims are often based on the relationship between two or more variables. “What causes what?” and “Up to what extent?” are a few of the questions that a hypothesis focuses on answering. The hypothesis can be true or false, based on complete evidence. While there are different hypotheses, we discuss only null and alternate hypotheses. The null hypothesis, denoted H o , is the default position where variables do not have a relation with each other. That means the null hypothesis is assumed true until evidence indicates otherwise. The alternative hypothesis, denoted H 1 , on the other hand, opposes the null hypothesis. It assumes a relation between the variables and serves as evidence to reject the null hypothesis. Example of Hypothesis: Mean age of all college students is 20.4 years. (simple hypothesis). An Alternative Hypothesis is a claim or a complement to the null hypothesis. If the null hypothesis predicts a statement to be true, the Alternative Hypothesis predicts it to be false. Let’s say the null hypothesis states there is no difference between height and shoe size then the alternative hypothesis will oppose the claim by stating that there is a relation. We see that the null hypothesis assumes no relationship between the variables whereas an alternative hypothesis proposes a significant relation between variables. An alternative theory is the one tested by the researcher and if the researcher gathers enough data to support it, then the alternative hypothesis replaces the null hypothesis. Null and alternative hypotheses are exhaustive, meaning that together they cover every possible outcome. They are also mutually exclusive, meaning that only one can be true at a time. There are a few types of alternative hypothesis that we will see: 1. One-tailed test H 1 : A one-tailed alternative hypothesis focuses on only one region of rejection of the sampling distribution. The region of rejection can be upper or lower. - Upper-tailed test H 1 : Population characteristic > Hypothesized value
- Lower-tailed test H 1 : Population characteristic < Hypothesized value
2. Two-tailed test H 1 : A two-tailed alternative hypothesis is concerned with both regions of rejection of the sampling distribution. 3. Non-directional test H 1 : A non-directional alternative hypothesis is not concerned with either region of rejection; rather, it is only concerned that null hypothesis is not true. 4. Point test H 1 : Point alternative hypotheses occur when the hypothesis test is framed so that the population distribution under the alternative hypothesis is a fully defined distribution, with no unknown parameters; such hypotheses are usually of no practical interest but are fundamental to theoretical considerations of statistical inference and are the basis of the Neyman–Pearson lemma. the differences between Null Hypothesis and Alternative Hypothesis is explained in the table below: | Null Hypothesis(H ) | Alternative Hypothesis(H ) | Definition | A default statement that states no relationship between variables. | A claim that assumes a relationship between variables. | Denoted by | H | H or H | In Research | States a presumption made before-hand | States the potential outcome a researcher may expect | Symbols Used | Equality Symbol (=, ≥, or ≤) | Inequality Symbol (≠, <, or >) | Example | Experience matters in a tech-job | Experience does not matter in a tech-job | Formulating an alternative hypothesis means identifying the relationships, effects or condition being studied. Based on the data we conclude that there is a different inference from the null-hypothesis being considered. - Understand the null hypothesis.
- Consider the alternate hypothesis
- Choose the type of alternate hypothesis (one-tailed or two-tailed)
Alternative hypothesis must be true when the null hypothesis is false. When trying to identify the information need for alternate hypothesis statement, look for the following phrases: - “Is it reasonable to conclude…”
- “Is there enough evidence to substantiate…”
- “Does the evidence suggest…”
- “Has there been a significant…”
When alternative hypotheses in mathematical terms, they always include an inequality ( usually ≠, but sometimes < or >) . When writing the alternate hypothesis, make sure it never includes an “=” symbol. To help you write your hypotheses, you can use the template sentences below. Does independent variable affect dependent variable? - Null Hypothesis (H 0 ): Independent variable does not affect dependent variable.
- Alternative Hypothesis (H a ): Independent variable affects dependent variable.
Various examples of Alternative Hypothesis includes: Two-Tailed Example - Research Question : Do home games affect a team’s performance?
- Null-Hypothesis: Home games do not affect a team’s performance.
- Alternative Hypothesis: Home games have an effect on team’s performance.
- Research Question: Does sleeping less lead to depression?
- Null-Hypothesis: Sleeping less does not have an effect on depression.
- Alternative Hypothesis : Sleeping less has an effect on depression.
One-Tailed Example - Research Question: Are candidates with experience likely to get a job?
- Null-Hypothesis: Experience does not matter in getting a job.
- Alternative Hypothesis: Candidates with work experience are more likely to receive an interview.
- Alternative Hypothesis : Teams with home advantage are more likely to win a match.
Some applications of Alternative Hypothesis includes: - Rejecting Null-Hypothesis : A researcher performs additional research to find flaws in the null hypothesis. Following the research, which uses the alternative hypothesis as a guide, they may decide whether they have enough evidence to reject the null hypothesis.
- Guideline for Research : An alternative and null hypothesis include statements with the same purpose of providing the researcher with a basic guideline. The researcher uses the statement from each hypothesis to guide their research.
- New Theories : Alternative hypotheses can provide the opportunity to discover new theories that a researcher can use to disprove an existing theory that may not have been backed up by evidence.
We defined the relationship that exist between null-hypothesis and alternative hypothesis. While the null hypothesis is always a default assumption about our test data, the alternative hypothesis puts in all the effort to make sure the null hypothesis is disproved. Null-hypothesis always explores new relationships between the independent variables to find potential outcomes from our test data. We should note that for every null hypothesis, one or more alternate hypotheses can be developed. Also Check: Mathematics Maths Formulas Branches of Mathematics FAQs on Alternative HypothesisWhat is hypothesis. A hypothesis is a statement of a relationship between two or more variables.” It is a working statement or theory that is based on insufficient evidence. What is an Alternative Hypothesis?Alternative hypothesis, denoted by H 1 , opposes the null-hypothesis. It assumes a relation between the variables and serves as an evidence to reject the null-hypothesis. What is the Difference between Null-Hypothesis and Alternative Hypothesis?Null hypothesis is the default claim that assumes no relationship between variables while alternative hypothesis is the opposite claim which considers statistical significance between the variables. What is Alternative and Experimental Hypothesis?Null hypothesis (H 0 ) states there is no effect or difference, while the alternative hypothesis (H 1 or H a ) asserts the presence of an effect, difference, or relationship between variables. In hypothesis testing, we seek evidence to either reject the null hypothesis in favor of the alternative hypothesis or fail to do so. Please Login to comment...Similar reads. - School Learning
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Improve your Coding Skills with PracticeWhat kind of Experience do you want to share?What Is A Research (Scientific) Hypothesis? A plain-language explainer + examplesBy: Derek Jansen (MBA) | Reviewed By: Dr Eunice Rautenbach | June 2020 If you’re new to the world of research, or it’s your first time writing a dissertation or thesis, you’re probably noticing that the words “research hypothesis” and “scientific hypothesis” are used quite a bit, and you’re wondering what they mean in a research context . “Hypothesis” is one of those words that people use loosely, thinking they understand what it means. However, it has a very specific meaning within academic research. So, it’s important to understand the exact meaning before you start hypothesizing. Research Hypothesis 101- What is a hypothesis ?
- What is a research hypothesis (scientific hypothesis)?
- Requirements for a research hypothesis
- Definition of a research hypothesis
- The null hypothesis
What is a hypothesis?Let’s start with the general definition of a hypothesis (not a research hypothesis or scientific hypothesis), according to the Cambridge Dictionary: Hypothesis: an idea or explanation for something that is based on known facts but has not yet been proved. In other words, it’s a statement that provides an explanation for why or how something works, based on facts (or some reasonable assumptions), but that has not yet been specifically tested . For example, a hypothesis might look something like this: Hypothesis: sleep impacts academic performance. This statement predicts that academic performance will be influenced by the amount and/or quality of sleep a student engages in – sounds reasonable, right? It’s based on reasonable assumptions , underpinned by what we currently know about sleep and health (from the existing literature). So, loosely speaking, we could call it a hypothesis, at least by the dictionary definition. But that’s not good enough… Unfortunately, that’s not quite sophisticated enough to describe a research hypothesis (also sometimes called a scientific hypothesis), and it wouldn’t be acceptable in a dissertation, thesis or research paper . In the world of academic research, a statement needs a few more criteria to constitute a true research hypothesis . What is a research hypothesis?A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes – specificity , clarity and testability . Let’s take a look at these more closely. Need a helping hand?Hypothesis Essential #1: Specificity & ClarityA good research hypothesis needs to be extremely clear and articulate about both what’ s being assessed (who or what variables are involved ) and the expected outcome (for example, a difference between groups, a relationship between variables, etc.). Let’s stick with our sleepy students example and look at how this statement could be more specific and clear. Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night. As you can see, the statement is very specific as it identifies the variables involved (sleep hours and test grades), the parties involved (two groups of students), as well as the predicted relationship type (a positive relationship). There’s no ambiguity or uncertainty about who or what is involved in the statement, and the expected outcome is clear. Contrast that to the original hypothesis we looked at – “Sleep impacts academic performance” – and you can see the difference. “Sleep” and “academic performance” are both comparatively vague , and there’s no indication of what the expected relationship direction is (more sleep or less sleep). As you can see, specificity and clarity are key. Hypothesis Essential #2: Testability (Provability)A statement must be testable to qualify as a research hypothesis. In other words, there needs to be a way to prove (or disprove) the statement. If it’s not testable, it’s not a hypothesis – simple as that. For example, consider the hypothesis we mentioned earlier: Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night. We could test this statement by undertaking a quantitative study involving two groups of students, one that gets 8 or more hours of sleep per night for a fixed period, and one that gets less. We could then compare the standardised test results for both groups to see if there’s a statistically significant difference. Again, if you compare this to the original hypothesis we looked at – “Sleep impacts academic performance” – you can see that it would be quite difficult to test that statement, primarily because it isn’t specific enough. How much sleep? By who? What type of academic performance? So, remember the mantra – if you can’t test it, it’s not a hypothesis 🙂 Defining A Research HypothesisYou’re still with us? Great! Let’s recap and pin down a clear definition of a hypothesis. A research hypothesis (or scientific hypothesis) is a statement about an expected relationship between variables, or explanation of an occurrence, that is clear, specific and testable. So, when you write up hypotheses for your dissertation or thesis, make sure that they meet all these criteria. If you do, you’ll not only have rock-solid hypotheses but you’ll also ensure a clear focus for your entire research project. What about the null hypothesis?You may have also heard the terms null hypothesis , alternative hypothesis, or H-zero thrown around. At a simple level, the null hypothesis is the counter-proposal to the original hypothesis. For example, if the hypothesis predicts that there is a relationship between two variables (for example, sleep and academic performance), the null hypothesis would predict that there is no relationship between those variables. At a more technical level, the null hypothesis proposes that no statistical significance exists in a set of given observations and that any differences are due to chance alone. And there you have it – hypotheses in a nutshell. If you have any questions, be sure to leave a comment below and we’ll do our best to help you. If you need hands-on help developing and testing your hypotheses, consider our private coaching service , where we hold your hand through the research journey. 17 CommentsVery useful information. I benefit more from getting more information in this regard. Very great insight,educative and informative. Please give meet deep critics on many research data of public international Law like human rights, environment, natural resources, law of the sea etc In a book I read a distinction is made between null, research, and alternative hypothesis. As far as I understand, alternative and research hypotheses are the same. Can you please elaborate? Best Afshin This is a self explanatory, easy going site. I will recommend this to my friends and colleagues. Very good definition. How can I cite your definition in my thesis? Thank you. Is nul hypothesis compulsory in a research? It’s a counter-proposal to be proven as a rejection Please what is the difference between alternate hypothesis and research hypothesis? It is a very good explanation. However, it limits hypotheses to statistically tasteable ideas. What about for qualitative researches or other researches that involve quantitative data that don’t need statistical tests? In qualitative research, one typically uses propositions, not hypotheses. could you please elaborate it more I’ve benefited greatly from these notes, thank you. This is very helpful well articulated ideas are presented here, thank you for being reliable sources of information Excellent. Thanks for being clear and sound about the research methodology and hypothesis (quantitative research) I have only a simple question regarding the null hypothesis. – Is the null hypothesis (Ho) known as the reversible hypothesis of the alternative hypothesis (H1? – How to test it in academic research? this is very important note help me much more Hi” best wishes to you and your very nice blog” Trackbacks/Pingbacks- What Is Research Methodology? Simple Definition (With Examples) - Grad Coach - […] Contrasted to this, a quantitative methodology is typically used when the research aims and objectives are confirmatory in nature. For example,…
Submit a Comment Cancel replyYour email address will not be published. Required fields are marked * Save my name, email, and website in this browser for the next time I comment. Null Hypothesis Definition and Examples, How to StateWhat is the null hypothesis, how to state the null hypothesis, null hypothesis overview. Why is it Called the “Null”?The word “null” in this context means that it’s a commonly accepted fact that researchers work to nullify . It doesn’t mean that the statement is null (i.e. amounts to nothing) itself! (Perhaps the term should be called the “nullifiable hypothesis” as that might cause less confusion). Why Do I need to Test it? Why not just prove an alternate one?The short answer is, as a scientist, you are required to ; It’s part of the scientific process. Science uses a battery of processes to prove or disprove theories, making sure than any new hypothesis has no flaws. Including both a null and an alternate hypothesis is one safeguard to ensure your research isn’t flawed. Not including the null hypothesis in your research is considered very bad practice by the scientific community. If you set out to prove an alternate hypothesis without considering it, you are likely setting yourself up for failure. At a minimum, your experiment will likely not be taken seriously. - Null hypothesis : H 0 : The world is flat.
- Alternate hypothesis: The world is round.
Several scientists, including Copernicus , set out to disprove the null hypothesis. This eventually led to the rejection of the null and the acceptance of the alternate. Most people accepted it — the ones that didn’t created the Flat Earth Society !. What would have happened if Copernicus had not disproved the it and merely proved the alternate? No one would have listened to him. In order to change people’s thinking, he first had to prove that their thinking was wrong . How to State the Null Hypothesis from a Word ProblemYou’ll be asked to convert a word problem into a hypothesis statement in statistics that will include a null hypothesis and an alternate hypothesis . Breaking your problem into a few small steps makes these problems much easier to handle. Step 2: Convert the hypothesis to math . Remember that the average is sometimes written as μ. H 1 : μ > 8.2 Broken down into (somewhat) English, that’s H 1 (The hypothesis): μ (the average) > (is greater than) 8.2 Step 3: State what will happen if the hypothesis doesn’t come true. If the recovery time isn’t greater than 8.2 weeks, there are only two possibilities, that the recovery time is equal to 8.2 weeks or less than 8.2 weeks. H 0 : μ ≤ 8.2 Broken down again into English, that’s H 0 (The null hypothesis): μ (the average) ≤ (is less than or equal to) 8.2 How to State the Null Hypothesis: Part TwoBut what if the researcher doesn’t have any idea what will happen. Example Problem: A researcher is studying the effects of radical exercise program on knee surgery patients. There is a good chance the therapy will improve recovery time, but there’s also the possibility it will make it worse. Average recovery times for knee surgery patients is 8.2 weeks. Step 1: State what will happen if the experiment doesn’t make any difference. That’s the null hypothesis–that nothing will happen. In this experiment, if nothing happens, then the recovery time will stay at 8.2 weeks. H 0 : μ = 8.2 Broken down into English, that’s H 0 (The null hypothesis): μ (the average) = (is equal to) 8.2 Step 2: Figure out the alternate hypothesis . The alternate hypothesis is the opposite of the null hypothesis. In other words, what happens if our experiment makes a difference? H 1 : μ ≠ 8.2 In English again, that’s H 1 (The alternate hypothesis): μ (the average) ≠ (is not equal to) 8.2 That’s How to State the Null Hypothesis! Check out our Youtube channel for more stats tips! Gonick, L. (1993). The Cartoon Guide to Statistics . HarperPerennial. Kotz, S.; et al., eds. (2006), Encyclopedia of Statistical Sciences , Wiley. Stack Exchange NetworkStack Exchange network consists of 183 Q&A communities including Stack Overflow , the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. Q&A for work Connect and share knowledge within a single location that is structured and easy to search. Definition of alternative hypothesisWhich of these properties is required of the alternative hypothesis, by definition, in the general case: a) If the alternative hypothesis is true, then the null hypothesis would necessarily tend to be rejected if a sufficient amount of data were taken. b) If the null hypothesis is rejected, it follows that the alternative hypothesis must be true (perhaps given some assumptions)? This seems like a simple question, but the definitions I've found online are all something like "the null and alternative hypotheses are two rival hypothesis that are tested." If you can cite a source, it would be ideal, but you don't have to. - 1 $\begingroup$ This question (especially the particular framing of the comparison) reads like a question for a class, or a question from a textbook. Is something like that the case? "Perhaps given some assumptions" is impossibly vague -- what assumptions are included or excluded from consideration? Incidentally, neither is "true by definition" for any definition I've seen. (in particular a statement like "tend to be" isn't going to be part of a definition in any case; it's potentially a property of something once it's defined). Have you been given a definition? Did that definition mention assumptions? $\endgroup$ – Glen_b Commented Sep 25, 2015 at 3:54
- $\begingroup$ see stats.stackexchange.com/questions/163957/… $\endgroup$ – user83346 Commented Sep 25, 2015 at 4:16
- $\begingroup$ Thanks, the note about power was helpful. I did some more searching. I think the technical term for my criterion (a) is that a test is "consistent" or "pointwise consistent in power," which means that as you take more and more data, the power gets closer and closer to 1. (I'm not 100% sure of this.) It's a desirable feature of an alternative hypothesis but maybe not part of the definition. By "given some assumptions" in (b), I guess I mean any assumptions you can justify based on your knowledge of the problem. (Like assuming particular drug might cure an illness but won't cause it.) $\endgroup$ – JVonKorff Commented Sep 25, 2015 at 20:36
2 Answers 2The Frequentist definition would be that the alternative hypothesis is the logical complement to the null hypothesis. The two hypotheses must be mutually exclusive, jointly cover the parameter space and be complementary. Bayesian methods don't require binary hypotheses. EDIT To respond to comments. There is a tendency among some researchers to use $\mu=k$ as a null and an alternative of $\mu>k$. This might or might not be proper, particularly if the above definition is used. This is usually used when it is implicitly known that $\mu<k$ is not part of the parameter space. For example, you cannot have negative calories. It is improper otherwise. The use of an alternative such as $\mu>k$ is a problem for inference if, for example, in a z test one would find $z=-5$. Clearly, the null is rejected for most standard values of $\alpha$. However the inference and any decision which could follow from a null of $\mu=0$ since it is also clear that $\mu<0$. The proper, one-sided, null hypothesis should have been $\mu\le{0}$, with an alternative of $\mu>0$. The role of formal hypothesis declarations in Frequentist inference and decision theory is two-fold. First, it links the probability to a null hypothesis with well-defined frequencies. Second, it links the statements to a probabilistic version of modus tollens. Without a binary nature, that linkage is broken and the implied link between Aristotelean logic, frequencies, and set theory is also broken. - $\begingroup$ The two hypotheses are not exhaustive when using one tailed tests. Does your answer consider one tailed tests? $\endgroup$ – Joel W. Commented Aug 3, 2017 at 13:18
Answered in comments copied below: This question (especially the particular framing of the comparison) reads like a question for a class, or a question from a textbook. Is something like that the case? "Perhaps given some assumptions" is impossibly vague -- what assumptions are included or excluded from consideration? Incidentally, neither is "true by definition" for any definition I've seen. (in particular a statement like "tend to be" isn't going to be part of a definition in any case; it's potentially a property of something once it's defined). Have you been given a definition? Did that definition mention assumptions? – Glen_b Thanks, the note about power was helpful. I did some more searching. I think the technical term for my criterion (a) is that a test is "consistent" or "pointwise consistent in power," which means that as you take more and more data, the power gets closer and closer to 1. (I'm not 100% sure of this.) It's a desirable feature of an alternative hypothesis but maybe not part of the definition. By "given some assumptions" in (b), I guess I mean any assumptions you can justify based on your knowledge of the problem. (Like assuming particular drug might cure an illness but won't cause it.) Your AnswerSign up or log in, post as a guest. Required, but never shown By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy . Not the answer you're looking for? Browse other questions tagged hypothesis-testing definition or ask your own question .- Featured on Meta
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COMMENTS
The null hypothesis (H0) answers "No, there's no effect in the population.". The alternative hypothesis (Ha) answers "Yes, there is an effect in the population.". The null and alternative are always claims about the population. That's because the goal of hypothesis testing is to make inferences about a population based on a sample.
Null hypothesis: µ ≥ 70 inches. Alternative hypothesis: µ < 70 inches. A two-tailed hypothesis involves making an "equal to" or "not equal to" statement. For example, suppose we assume the mean height of a male in the U.S. is equal to 70 inches. The null and alternative hypotheses in this case would be: Null hypothesis: µ = 70 inches.
The null and alternative hypotheses are two competing claims that researchers weigh evidence for and against using a statistical test: Null hypothesis (H0): There's no effect in the population. Alternative hypothesis (HA): There's an effect in the population. The effect is usually the effect of the independent variable on the dependent ...
The actual test begins by considering two hypotheses.They are called the null hypothesis and the alternative hypothesis.These hypotheses contain opposing viewpoints. H 0, the —null hypothesis: a statement of no difference between sample means or proportions or no difference between a sample mean or proportion and a population mean or proportion. In other words, the difference equals 0.
In hypothesis-testing, there are always two competing hypotheses under consideration [1]: The status quo (null) hypothesis (H 0), The research (alternate) hypothesis (H a or H 1). You can think of the alternate hypothesis as just an alternative to the null. For example, if your null is "I'm going to win up to $1,000" then your alternate ...
Example Consider a test of hypothesis for the mean of a normal distribution, where we test . The test statistic is the z-statistic where is the sample mean, is the variance of the distribution and is the sample size. If we run a two-tailed test with critical value , the critical region is the union of the right and left tails of the ...
Basic definition. The alternative hypothesis and null hypothesis are types of conjectures used in statistical tests, which are formal methods of reaching conclusions or making judgments on the basis of data. In statistical hypothesis testing, the null hypothesis and alternative hypothesis are two mutually exclusive statements.
H0: The null hypothesis: It is a statement about the population that either is believed to be true or is used to put forth an argument unless it can be shown to be incorrect beyond a reasonable doubt. Ha: The alternative hypothesis: It is a claim about the population that is contradictory to H0 and what we conclude when we reject H0. Since the ...
The actual test begins by considering two hypotheses.They are called the null hypothesis and the alternative hypothesis.These hypotheses contain opposing viewpoints. \(H_0\): The null hypothesis: It is a statement of no difference between the variables—they are not related. This can often be considered the status quo and as a result if you cannot accept the null it requires some action.
Thus, our alternative hypothesis is the mathematical way of stating our research question. If we expect our obtained sample mean to be above or below the null hypothesis value, which we call a directional hypothesis, then our alternative hypothesis takes the form: HA: μ> 7.47 or HA: μ <7.47 H A: μ> 7.47 or H A: μ <7.47.
The alternative hypothesis is a hypothesis used in significance testing which contains a strict inequality. A test of significance will result in either rejecting the null hypothesis (indicating ...
Examples. A research hypothesis, in its plural form "hypotheses," is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.
The definition of alternative hypothesis with examples. An alternative hypothesis is a hypothesis that there is a relationship between variables. This includes any hypothesis that predicts positive correlation, negative correlation, non-directional correlation or causation.The only hypothesis that isn't an alternative hypothesis is a null hypothesis that predicts no relationship between ...
Most technical papers rely on just the first formulation, even though you may see some of the others in a statistics textbook. Null hypothesis: " x is equal to y.". Alternative hypothesis " x is not equal to y.". Null hypothesis: " x is at least y.". Alternative hypothesis " x is less than y.". Null hypothesis: " x is at most ...
An alternative hypothesis is a contradictory theory to that taken by a Null Hypothesis about a specified research parameter. As the name suggests, the alternative hypothesis proposes an alternative theory and rejects the null hypothesis statement for a research parameter. The value of research can be greater than, not equal to, or less than the ...
The hypothesis can be inductive or deductive, simple or complex, null or alternative. While the null hypothesis is the hypothesis, which is to be actually tested, whereas alternative hypothesis gives an alternative to the null hypothesis. ... Definition of Alternative Hypothesis. A statistical hypothesis used in hypothesis testing, which states ...
Definition. The alternative hypothesis is a statement used in statistical inference experiment. It is contradictory to the null hypothesis and denoted by H a or H 1. We can also say that it is simply an alternative to the null. In hypothesis testing, an alternative theory is a statement which a researcher is testing.
The alternative hypothesis is simply the reverse of the null hypothesis, and there are three options, depending on where we expect the difference to lie. Thus, our alternative hypothesis is the mathematical way of stating our research question. If we expect our obtained sample mean to be above or below the null hypothesis value, which we call a ...
The alternative hypothesis, denoted H 1, on the other hand, opposes the null hypothesis. It assumes a relation between the variables and serves as evidence to reject the null hypothesis. Example of Hypothesis: Mean age of all college students is 20.4 years. (simple hypothesis). Alternative Hypothesis
An alternative hypothesis is an opposing theory to the null hypothesis. For example, if the null hypothesis predicts something to be true, the alternative hypothesis predicts it to be false. The alternative hypothesis often is the statement you test when attempting to disprove the null hypothesis. If you can gather enough data to support the ...
A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes - specificity, clarity and testability. Let's take a look at these more closely.
Step 1: Figure out the hypothesis from the problem. The hypothesis is usually hidden in a word problem, and is sometimes a statement of what you expect to happen in the experiment. The hypothesis in the above question is "I expect the average recovery period to be greater than 8.2 weeks.". Step 2: Convert the hypothesis to math.
Which of these properties is required of the alternative hypothesis, by definition, in the general case: a) If the alternative hypothesis is true, then the null hypothesis would necessarily tend to be rejected if a sufficient amount of data were taken. b) If the null hypothesis is rejected, it follows that the alternative hypothesis must be ...