method of statistical inference
Wikipedia
en.wikipedia.org › wiki › Statistical_hypothesis_test
Statistical hypothesis test - Wikipedia
2 weeks ago - An example hypothesis could be ... any statement about the parameters describing a population can be a hypothesis (but not a statement about the sample). The test compares two hypotheses: a default null hypothesis (denoted H0) and its negation, the alternative hypothesis ...
Definition of termsHistoryModern origins and early controversyTechnical description of the null hypothesisPhilosophyEducationPrincipleGoals of null hypothesis testsChoice of the null hypothesisPerforming a frequentist hypothesis test in practiceNonparametric bootstrap hypothesis testingExamplesVariations and sub-classesNeyman–Pearson hypothesis testingCriticismAlternativesFurther reading
National University
resources.nu.edu › statsresources › hypothesis
Null & Alternative Hypotheses - Statistics Resources - LibGuides at National University
1 week ago - Null Hypothesis (H0) – This can be thought of as the implied hypothesis. “Null” meaning “nothing.” This hypothesis states that there is no difference between groups or no relationship between variables.
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What is a Null Hypothesis? (4 Minute Easy Explanation) - YouTube
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Null Hypothesis | Definition & Examples - Video | Study.com
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Hypothesis Testing and The Null Hypothesis, Clearly Explained!!!
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Null Hypothesis Vs Alternative Hypothesis (Easy Explanation) - YouTube
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What is a Null Hypothesis? - YouTube
Why is the null hypothesis important?
The importance of the null hypothesis is that it provides an approximate description of the phenomena of the given data. It allows the investigators to directly test the relational statement in a research study.
byjus.com
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Null Hypothesis Definition
What is meant by the null hypothesis?
In Statistics, a null hypothesis is a type of hypothesis which explains the population parameter whose purpose is to test the validity of the given experimental data.
byjus.com
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Null Hypothesis Definition
When a null hypothesis is accepted and rejected?
The null hypothesis is either accepted or rejected in terms of the given data. If P-value is less than α, then the null hypothesis is rejected in favor of the alternative hypothesis, and if the P-value is greater than α, then the null hypothesis is accepted in favor of the alternative hypothesis.
byjus.com
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Null Hypothesis Definition
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.
Hypothesis testing and how to state Null and alternative hypothesis May 28, 2022
r/AskStatistics 4y ago
Investopedia
investopedia.com › terms › n › null_hypothesis.asp
Understanding Null Hypothesis in Investment Analysis
April 2, 2026 - A null hypothesis is a foundational concept in statistics that assumes there is no real relationship or effect in the data being analyzed, and that any variations or trends are simply the result of random fluctuation rather than a true underlying cause.
Brookbush Institute
brookbushinstitute.com › home › glossary › null hypothesis
Null Hypothesis - Brookbush Institute
To write a null hypothesis, begin by formulating a research question. Then rephrase that question in a way that assumes no relationship between the variables of interest. In other words, the null hypothesis is always framed as if the treatment, condition, or exposure has no effect on the outcome.
Reddit
reddit.com › r/askstatistics › how do i use null hypothesis testing and p-values for maximally specific hypotheses?
r/AskStatistics on Reddit: How do I use null hypothesis testing and p-values for maximally specific hypotheses?
September 14, 2024 -
I apologize as I'm probably misunderstanding something fundamental here.
My understanding is that the p-value is the sum of the probabilities of observing:
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The outcome predicted by your hypothesis.
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Any outcome that is equally rare or more rare.
Let's say I have the hypothesis that my coin is biased in such a way that over the next 20 flips, I will get precisely this outcome: HTHTHHHTTTTTHHTHTTHT.
The null hypothesis is that actually it's just a normal fair coin.
The odds of observing the outcome predicted by my hypothesis if the coin is actually a fair coin is 1 out of 220 .
The following outcomes are equally rare:
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Getting precisely the outcome HHHHHHHHHHHHHHHHHHHH.
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Getting precisely the outcome HHHHHHHHHHHHHHHHHHHT.
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Getting precisely the outcome HHHHHHHHHHHHHHHHHHTH.
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Getting precisely the outcome HHHHHHHHHHHHHHHHHHTT.
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etc.
In fact, every single outcome of this precision is equally likely, so the sum of all these probabilities would be 1, so my p-value would be 1?
And now let's say I decide to proceed with my experiment anyway, and I flip the coin 20 times, and lo and behold, I do end up getting precisely the predicted outcome of HTHTHHHTTTTTHHTHTTHT.
Intuitively, it seems like the result of this experiment is extremely strong evidence in favor of the hypothesis, but given a p-value of 1, which is greater than 0.05, it seems like I would have failed to reject the null hypothesis.
And it seems like this problem would occur any time your hypothesis is so specific that it picks out one atomic outcome (as opposed to trying to group together related outcomes) out of all possible outcomes.
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The p-value only considers the chance of the outcome being generated under the null hypothesis.
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2. Any outcome that is equally rare or more rare. It's not that these outcomes need to be at least as rare, they need to be at least as extreme. What "extreme" means varies by test, but for your test with 20 coin flips and a null hypothesis that the coin is fair, a natural notion of extremity would be "the difference between the observed number of heads and expected number of heads" (for a one-sided test, say) or "the absolute difference between the observed number of heads and expected number of heads" (for a two-sided test).
Stack Exchange
math.stackexchange.com › questions › 4695306 › understanding-null-hypothesis-expression
binomial distribution - Understanding null hypothesis expression - Mathematics Stack Exchange
May 8, 2023 - Or in other words, the null hypothesis being true implies that $X$ has the given distribution.
BYJUS
byjus.com › maths › null-hypothesis
Null Hypothesis Definition
April 25, 2022 - The null hypothesis is a kind of hypothesis which explains the population parameter whose purpose is to test the validity of the given experimental data. This hypothesis is either rejected or not rejected based on the viability of the given population or sample.
National Library of Medicine
nlm.nih.gov › oet › ed › stats › 02-700.html
Finding and Using Health Statistics
In statistical analysis, two hypotheses are used. The null hypothesis, or H0, states that there is no statistical significance between two variables. The null is often the commonly accepted position and what scientists seek to find evidence against.
Quora
quora.com › How-do-you-find-the-null-hypothesis-when-you-have-the-alternative-hypothesis
How to find the null hypothesis when you have the alternative hypothesis - Quora
Answer (1 of 4): The “alternative hypothesis” is so named because it is the alternative to the null hypothesis. You literally cannot have an alternate hypothesis if you don’t have the null. For instance, you alternative hypothesis could just be the logical negation of whatever hypothesis ...
Cambridge Dictionary
dictionary.cambridge.org › us › dictionary › english › null-hypothesis
NULL HYPOTHESIS definition | Cambridge English Dictionary
The null hypothesis states that the corresponding regression coefficient is equal across all levels of the response variable.
Journal of Cardiothoracic and Vascular Anesthesia
jcvaonline.com › article › S1053-0770(23)00117-9 › fulltext
The Art of the Null Hypothesis—Considerations for Study Design and Scientific Reporting - Journal of Cardiothoracic and Vascular Anesthesia
February 21, 2023 - In medical research, conventional null hypothesis testing compares a null hypothesis H0 (typically that there is no difference between 2 or more differently exposed groups) with an alternative hypothesis Ha (usually that a difference exists).1 Because 2 comparator groups rarely have identical ...
Psychstat
advstats.psychstat.org › book › hypothesis › index.php
Null hypothesis testing -- Advanced Statistics using R
The null hypothesis assumes no difference/relationship/effect in the population from which the sample is selected. The likelihood is measured by a $p$ value. If the $p$ value is small enough, we reject the null. In the significance testing approach of Ronald Fisher, a null hypothesis is rejected on the basis of data that are significantly unlikely if the null is true.
Omniconvert
omniconvert.com › what-is › null-hypothesis
What a Null Hypothesis Is: Definition & A/B Testing Role
February 14, 2025 - Quick Answer A null hypothesis (H0) is the default assumption in a statistical test that there is no effect, no difference, or no relationship between the things you compare. It is the starting position a test is built to challenge: you assume ...
YouTube
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What's a null hypothesis? // How to write a null hypothesis - YouTube
One way to say this is: A null hypothesis is a statement that says how the independent variable would have no effect on the dependent variable. Watch the vid...
Published: February 11, 2025
Dissertation-statistics
dissertation-statistics.com › home › null hypotheses
Null Hypothesis and Research Hypotheses Guide
July 20, 2026 - Basically, there are two types of null hypotheses with examples for you to use as models with your dissertation samples. 1. Non Directional Null Hypothesis The first type of Null Hypotheses test for differences or relationships with your samples.
Open Textbook BC
opentextbc.ca › researchmethods › chapter › understanding-null-hypothesis-testing
Understanding Null Hypothesis Testing – Research Methods in Psychology – 2nd Canadian Edition
October 13, 2015 - One interpretation is called the null hypothesis (often symbolized H0 and read as “H-naught”). This is the idea that there is no relationship in the population and that the relationship in the sample reflects only sampling error.
Statsig
statsig.com › perspectives › null-hypothesis-guide-experimentation
What is a null hypothesis? A guide for experimentation
February 25, 2025 - Null hypothesis testing is a systematic process. First, you establish both the null hypothesis (H₀) and the alternative hypothesis (H₁). Then, you collect your data and calculate a test statistic along with a p-value.
Laerd Statistics
statistics.laerd.com › statistical-guides › hypothesis-testing-3.php
Hypothesis Testing - Significance levels and rejecting or accepting the null hypothesis
The null hypothesis is essentially the "devil's advocate" position. That is, it assumes that whatever you are trying to prove did not happen (hint: it usually states that something equals zero). For example, the two different teaching methods did not result in different exam performances (i.e., ...