National University
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Null & Alternative Hypotheses - Statistics Resources - LibGuides at National University
In research, there are two types ... can be thought of as the implied hypothesis. “Null” meaning “nothing.” This hypothesis states that there is no difference ......
Scribbr
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Null and Alternative Hypotheses | Definitions & Examples
January 24, 2025 - TipBe careful with your words when you report the results of a statistical test in a research paper or thesis. If you reject the null hypothesis, you can say that the alternative hypothesis is supported. On the other hand, if you fail to reject the null hypothesis, then you can say that the alternative hypothesis is not supported. Never say that you’ve proven or disproven a hypothesis. Alternative hypotheses often include phrases such as “an effect,” “a difference,” or “a relationship.” When alternative hypotheses are written in mathematical terms, they always include an inequality (usually ≠, but sometimes < or >).
Videos
Examples of null and alternative hypotheses (video)
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Null and alternative hypotheses with Lindsey Leach - YouTube
Null hypothesis vs alternative hypothesis #math #mathematics #mathtok #teacher #teachersoftiktok #maths #statistics | TikTok
Null vs. alternative Hypothesis #biology #statistics #nullhypothesis #alternativehypothesis #hypothesis | TikTok
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Null and Alternate Hypothesis - Statistical Hypothesis Testing ...
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Writing the Null and Alternate Hypothesis in Statistics - YouTube
What’s the difference between a research hypothesis and a statistical hypothesis?
A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (“x affects y because …”). · A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study, the statistical hypotheses correspond logically to the research hypothesis.
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Null and Alternative Hypotheses | Definitions & Examples
What are null and alternative hypotheses?
Null and alternative hypotheses are used in statistical hypothesis testing. The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.
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Null and Alternative Hypotheses | Definitions & Examples
What is hypothesis testing?
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses, by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.
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Null and Alternative Hypotheses | Definitions & Examples
GeeksforGeeks
geeksforgeeks.org › data science › difference-between-null-and-alternate-hypothesis
Difference between Null and Alternate Hypothesis - GeeksforGeeks
May 18, 2022 - It acts as a compass in the process. Null hypothesis suggests that there is no relationship between the two variables. Null hypothesis is also exactly the opposite of the alternative hypothesis.
Outlier
articles.outlier.org › null-vs-alternative-hypothesis
Null vs. Alternative Hypothesis [Overview] | Outlier
April 28, 2023 - ... H_1H1) is the hypothesis that stands contrary to the null hypothesis. The alternative hypothesis represents the research hypothesis—what you as the statistician are trying to prove with your data.
Lumen Learning
courses.lumenlearning.com › introstats1 › chapter › null-and-alternative-hypotheses
Null and Alternative Hypotheses | Introduction to Statistics
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 ...
statistical concept
Wikipedia
en.wikipedia.org › wiki › Null_hypothesis
Null hypothesis - Wikipedia
3 weeks ago - In the hypothesis testing approach of Jerzy Neyman and Egon Pearson, a null hypothesis is contrasted with an alternative hypothesis, and the two hypotheses are distinguished on the basis of data, with certain error rates. It is used in formulating answers in research.
G2
g2.com › articles › null-vs-alternative-hypothesis
Null Vs. Alternative Hypothesis
May 8, 2024 - While the null hypothesis presumes no change or status quo, an alternative hypothesis or the claim shows that a non-random cause influences the observations. That’s the key difference between null and alternative hypotheses.
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Medium
medium.com › pythons-gurus › null-hypothesis-vs-alternative-hypothesis-the-foundation-of-statistical-inference-95215d59f69f
Null Hypothesis vs. Alternate Hypothesis: The Foundation of Statistical Inference | by Sarowar Ahmed | Python’s Gurus | Medium
July 29, 2024 - Alternate Hypothesis (H₁ or Hₐ): The alternate hypothesis is a statement that contradicts the null hypothesis. It represents the research hypothesis or the claim we want to provide evidence for.
ThoughtCo
thoughtco.com › null-hypothesis-vs-alternative-hypothesis-3126413
Differences Between The Null and Alternative Hypothesis
June 24, 2019 - The null hypothesis states there will be no change or effect in the experiment's outcome. The alternative hypothesis suggests there will be a change or effect in the experiment.
Reddit
reddit.com › r/askstatistics › null hypothesis and alternative hypothesis
r/AskStatistics on Reddit: Null hypothesis and Alternative Hypothesis
January 5, 2021 -
Hey! Can someone explain to me in simple terms the definition of null hypothesis? If u can use an example it would be great! Also if we reject the null hypothesis does it mean that the alternative hypothesis is true?
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Hi! So, yours is actually a sophisticated question that masquerades as a simple one, so I'll try to answer this in a way that conveys the concept while perhaps alluding to some of its problems. At its heart, the null hypothesis is a sort of "straw man" that is defined by a researcher at the beginning of an experiment that usually represents a state of affairs that would be expected to occur if the researcher's proposal were false. Note that a null hypothesis is entirely imaginary, and it has nothing to do with the actual state of the world. It is contrived, usually to show that the actual state of the world is inconsistent with the null hypothesis. Suppose a researcher is trying to determine whether the heights of men and women are different. A suitable null hypothesis might be that the difference of the two population averages (height of men and height of women) is equal to zero. Then the researcher would conduct his or her experiment by measuring the heights of many men and women. When it comes time to draw a statistical conclusion, he or she will compute the probability that the observed data (the set of heights) could have come from the null hypothesis (i.e., a world where there is no difference). This probability is called a "p-value". Conceptually, this is similar to a "proof by contradiction," in which we assert that, if the probability is very small that the data could have originated from the null hypothesis, it must not be true. This is what is meant by "rejecting the null hypothesis". It is different from a proof by contradiction because rejecting the null proves nothing, except perhaps that the null is unlikely to be the source of the observed data. It doesn't prove that the true difference is 5 inches, or 1 inch, or anything. Because of this, rejecting the null hypothesis is in NO WAY equivalent to accepting an alternative hypothesis. Usually, in the course of an experiment, we observe a result (such as the observed height difference, perhaps it is ~5 inches) that, once we reject, replaces the hypothesized value of 0 under the null. However, we DON'T know anything about the probability that our observed value is "correct", which is why we never say that we have "accepted" an alternative. I actually hesitate to discuss an "alternative" hypothesis because most researchers never state one and it doesn't matter for the purposes of null hypothesis significance testing (NHST). It is just the name given to the conclusion drawn by the researchers after they have rejected their null hypothesis. Philosophically, there is an adage that data can never be used to prove an assertion, only to disprove one. It includes an analogy about a turkey concluding that he is loved by his human family and is proven wrong upon being slaughtered on Thanksgiving. I'll include a link if I can find it. Now, think about this: The concept of rejecting a null hypothesis probably seems very reasonable as long as we are careful not to overinterpret it, and this is how NHST was performed for decades. But consider - what is the probability that the null hypothesis is true in the first place? In other words, how likely is it that the difference between mens' and womens' heights is equal to zero? I propose that the probability is exactly zero, and if you disagree then I will find a ruler small enough to prove me correct. The difference can never be equal to exactly zero (even though this is the "straw man" that our experiment refutes), so we are effectively testing against a hypothesis that can never be true. Rejecting a hypothesis we already know to be false tells us nothing important ("the data are unlikely to have come from this state that cannot be true"). And since every null hypothesis is imaginary, it is suggested that any null hypothesis can be rejected with enough statistical power (read:sample size). Often a "significant" result says more about a study's sample size than it does about the study's findings, even though the language used in papers/media suggests to readers that the findings are more "important" or "likely to be correct". This has, in part, led to a reproducibility crisis in the sciences and, for some, an undermining of subject-matter-experts' trust in the use of applied statistics.
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The null hypothesis (Ho) signifies no change. The alternative hypothesis (Ha) signifies a change. If we reject the null, we have evidence for the alternative hypothesis. This doesn’t mean that it’s true just that within this study, we have evidence to support the alternative hypothesis. If we fail to reject the null (we don’t use the word accept) then there is not enough evidence supporting the alternative hypothesis. Example: I’m wondering if smoking impacts lung function using a spirometry test that measures forced exploratory volume per second (FEV1). Ho: There is no difference in FEV1 between smokers vs non smokers Ha: There is a difference in FEV1 between smokers and non smokers. Rejecting or failing to reject the null aka Ho will involve more steps than just analyzing the mean FEV1 between the two groups, so let’s stop here before we get into more hypothesis testing.
Wall Street Mojo
wallstreetmojo.com › home › all blogs › statistics resources › null vs. alternative hypothesis
Null vs Alternative Hypothesis - Top 7 Differences (Infographics)
January 2, 2025 - The null and alternative hypothesis ... The key difference is that the null hypothesis disapproves of the phenomenon or event put forth by the alternative hypothesis or research hypothesis....
Study.com
study.com › psychology courses › psychology 105: research methods in psychology
Null vs. Alternative Hypothesis | Definition & Examples - Lesson | Study.com
December 16, 2013 - By contrast, the alternative hypothesis indicates that statistically significant differences occur between two or more experimental or control groups. An experimental group refers to the part of the study that receives the treatment studied by the researcher, while the control group receives no treatment. Although both the null and the alternative hypotheses make predictions that are tested in a study, there are several important differences between the two.
Shiksha
shiksha.com › home › data science › data science articles › machine learning articles › difference between null hypothesis and alternative hypothesis
Difference between Null Hypothesis and Alternative Hypothesis - Shiksha Online
September 16, 2024 - Generally, researchers want to disprove or reject the null hypothesis. ... A statistical hypothesis that states that there is a significant two variable (or set of variables) is called an Alternative Hypothesis.
Statistics Solutions
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Null hypothesis and Alternative Hypothesis - Statistics Solutions
May 14, 2025 - Need help with your research? Leverage our 30+ years of experience and low-cost same-day service to complete your results today! Schedule now using the calendar below. The null hypothesis and alternative hypothesis are useful only if they state the expected relationship between the variables or if they are consistent with the existing body of knowledge.
Texas Gateway
texasgateway.org › resource › 91-null-and-alternative-hypotheses
9.1 Null and Alternative Hypotheses | Texas Gateway
In other words, the difference equals 0. 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 null and alternative hypotheses are contradictory, you must examine evidence to decide if you have enough ...
Testbook
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Learn the Difference Between Null and Alternative Hypothesis
The alternative hypothesis, denoted as Ha or H1, is a statement that contradicts the null hypothesis. It suggests that there is a significant relationship or difference between variables in the population.
Medium
medium.com › @andersongimino › differences-between-the-null-and-alternative-hypotheses-6b2e794543f6
Differences between the null and alternative hypotheses | by Anderson Gimino | Medium
July 14, 2023 - The null and alternative hypotheses are mutually exclusive, meaning they cannot both be true at the same time. The null hypothesis is a statement that is assumed to be true unless there is convincing evidence to the contrary.
Microbe Notes
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Null hypothesis and alternative hypothesis with 9 differences
August 3, 2023 - Null hypothesis H0: µ= 10 tons Alternative hypothesis Ha: µ>10 tons · 2. Under another study that is trying to test whether there is a significant difference between the effectiveness of medicine against heart arrest, the alternative hypothesis will be that there is a relationship between the medicine and chances of heart arrest. R. Kothari (1990) Research Methodology. Vishwa Prakasan. India.
Formpl
formpl.us › blog › alternative-null-hypothesis
Alternative vs Null Hypothesis: Pros, Cons, Uses & Examples
November 22, 2021 - While the null hypothesis is always an assumption that needs to be proven with evidence for it to be accepted, the alternative hypothesis puts in all the effort to make sure the null hypothesis is disproved.
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Your question starts out as if the statistical null and alternative hypotheses are what you are interested in, but the penultimate sentence makes me think that you might be more interested in the difference between scientific and statistical hypotheses.
Statistical hypotheses can only be those that are expressible within a statistical model. They typically concern values of parameters within the statistical model. Scientific hypotheses almost invariably concern the real world, and they often do not directly translate into the much more limited universe of the chosen statistical model. Few introductory stats books spend any real time considering what constitutes a statistical model (it can be very complicated) and the trivial examples used have scientific hypotheses so simple that the distinction between model and real-world hypotheses is blurry.
I have written an extensive account of hypothesis and significance testing that includes several sections dealing with the distinction between scientific and statistical hypotheses, as well as the dangers that might come from assuming a match between the statistical model and the real-world scientific concerns: A Reckless Guide to P-values
So, to answer your explicit questions:
• No, statisticians do not always use null and alternative hypotheses. Many statistical methods do not require them.
• It is common practice in some disciplines (and maybe some schools of statistics) to specify the null and alternative hypothesis when a hypothesis test is being used. However, you should note that a hypotheses test requires an explicit alternative for the planning stage (e.g. for sample size determination) but once the data are in hand that alternative is no longer relevant. Many times the post-data alternative can be no more than 'not the null'.
• I'm not sure of the mental heuristic thing, but it does seem possible to me that the beginner courses omit so much detail in the service of simplicity that the word 'hypothesis' loses its already vague meaning.
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You wrote
the declaration of a null and alternative hypothesis is the "first step" of any good experiment and subsequent analysis.
Well, you did put quotes around first step, but I'd say the first step in an experiment is figuring out what you want to figure out.
As to "subsequent analysis", it might even be that the subsequent analysis does not involve testing a hypothesis! Maybe you just want to estimate a parameter. Personally, I think tests are overused.
Often, you know in advance that the null is false and you just want to see what is actually going on.