National University
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Null & Alternative Hypotheses - Statistics Resources - LibGuides at National University
July 9, 2026 - Null Hypothesis: H0: Experience on the job has no impact on the quality of a brick mason’s work. Alternative Hypothesis: Ha: The quality of a brick mason’s work is influenced by on-the-job experience. ... Next: One-Tail vs. Two-Tail >> ... Doctoral Center Institutional Review Board Advanced Research Center Institutional Repository NU Commons
method of statistical inference
Wikipedia
en.wikipedia.org › wiki › Null_hypothesis
Null hypothesis
2 weeks ago - In general, 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 (H1). It is usually consistent with the research ...
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
ELI5 - what is reject the null or do not reject the null?
In data science, null generally refers to the null hypothesis. Let's say we're doing an experiment with two groups: Group A and Group B. These groups receive two different diets and lose varying amounts of weight. The null hypothesis is the statement "There is no difference in lost weight between Group A and Group B." So, if the average weight loss is 10 pounds for both groups, we can clearly say that the null hypothesis is true. Now, let's say that A loses 10 pounds and B loses 11 pounds. If we're being honest, that's not really Tha big a difference. It could have just been luck, right? That's why data scientists use a variety of statistical methods to compare groups. I won't go into too much depth, but basically the methods used answer the question: "Given Group A's data and Group B's data, how likely is it that the treatments actually had the same effect?" If you feel confident that the data is different enough, you can "reject the null hypothesis." That basically means that you have enough evidence to say that the null hypothesis is wrong. More on reddit.com
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January 5, 2022Can someone explain null hypothesis?
Hypothesis: this is true Null: what I said is true, isn’t true. You either reject the null, or fail to reject the null. It’s like: H: + good job Ho: - not good job Reject the null: double negatives = positive (not good job is not true) p<.05 statistically significant Fail to reject the null: triple negative = too many negatives (not good job is true) p=3.49 not even close. You always want to reject the null, that means your study results were statistically significant! More on reddit.com
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July 25, 2023[Q] Question about choosing null and alternative hypotheses
The null is ALWAYS the opposite of what you want to prove. It is related to modus tollens. If A then B and Not B therefore not A. More on reddit.com
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April 9, 2023ELI5 what is the null hypothesis and can you give me some simple examples?
More or less, the null hypothesis is a hypothesis that states there wasn't anything important discovered in observation. If it's a two-group trial and control study, the null hypothesis is generally "the trial group is no different".
If the study is testing a medication, the null hypothesis is "it doesn't do anything".
If the study is comparing gender differences in some mental task, the null hypothesis is "there isn't a difference".
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November 27, 2022What’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 & Alternative Hypotheses | Definitions, Templates & 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 & Alternative Hypotheses | Definitions, Templates & 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.
scribbr.com
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Null & Alternative Hypotheses | Definitions, Templates & Examples
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What is a Null Hypothesis? (4 Minute Easy Explanation) - YouTube
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The Null Hypothesis and Research Hypothesis - YouTube
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What's a null hypothesis? // How to write a null hypothesis - YouTube
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Null Hypothesis | Definition & Examples - Video | Study.com
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Null hypothesis explained - YouTube
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 - Why "Fail to reject null hypothesis" instead of "Accepting Alternative Hypothesis" ? Sep 17, 2022
r/datascience 3y ago
Scribbr
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Null & Alternative Hypotheses | Definitions, Templates & Examples
January 24, 2025 - 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 or H1): There’s an effect in the population. The effect is usually the effect of the independent variable on the dependent variable.
Brookbush Institute
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Null Hypothesis - Brookbush Institute
It represents the assumption of no effect, no difference, or no relationship between variables. It serves as a starting point or baseline for statistical comparison. Research is conducted with the aim of either refuting (rejecting) or failing ...
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 - SINCE THE ADVENT of the scientific method, hypothesis testing has been a crucial tool for drawing inferences from research studies. 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 outcomes, statistical methods for hypothesis testing assess the likelihood that observed differences between the groups result from random chance.
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.
SciSpace
scispace.com › resources › null-hypothesis-in-research
Importance of Null Hypothesis in Research
February 24, 2025 - Null hypothesis testing, a common statistical method, relies on comparing observed data to what would be expected under the assumption of no effect. This statistical scrutiny is integral to drawing valid conclusions. The null hypothesis sharpens the focus of the research objectives.
GeeksforGeeks
geeksforgeeks.org › data science › null-vs-alternate-hypothesis
Null Hypothesis vs. Alternative Hypothesis - GeeksforGeeks
January 12, 2026 - Understanding the difference between them is essential for correct analysis and interpretation. ... The Null Hypothesis is the starting assumption in hypothesis testing.
VIARES
viares.com › home › null hypothesis
Null Hypothesis - Clinical Research Explained | VIARES
September 28, 2025 - It serves as the basis for testing the validity of a scientific claim. In essence, the null hypothesis assumes that there is no significant difference or relationship between variables under study.
PubMed Central
pmc.ncbi.nlm.nih.gov › articles › PMC6785820
Understanding Hypothesis Testing and Statistical Errors - PMC
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Optimizely
optimizely.com › optimization-glossary › null-hypothesis
Null hypothesis
June 21, 2026 - Risk management: By requiring evidence to reject the null hypothesis, this approach helps researchers avoid making false claims and protects against concluding that effects exist when they don't. The null hypothesis works within a framework of interconnected statistical concepts. When you create a null hypothesis, you simultaneously define the alternative hypothesis which states there is a significant difference or relationship between your variables and typically represents what you hope to prove.
ThoughtCo
thoughtco.com › null-hypothesis-examples-609097
What Is the Null Hypothesis?
May 7, 2024 - In statistical analysis, the null hypothesis assumes there is no meaningful relationship between two variables. Testing the null hypothesis can tell you whether your results are due to the effect of manipulating a dependent variable or due ...
iSixSigma
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Null Hypothesis vs. Hypothesis: What's the Difference? - isixsigma.com
The null hypothesis is assumed true until proven otherwise. A hypothesis, also known as an alternative hypothesis, is an educated theory or “guess” based on limited evidence that requires further testing to be proven true or false. It is used in an experiment to define a relationship between two variables. A hypothesis helps a researcher prove or disprove their theories, or guesses, using limited data and knowledge.
Published: February 4, 2025
Socscistatistics
socscistatistics.com › tests › studentttest
Student's T-Test Calculator for 2 Independent Means (Equal Variances) | Social Science Statistics | Social Science Statistics
H₀: μ₁ - μ₂ = 0, where μ₁ is the mean of first population and μ₂ the mean of the second. As above, the null hypothesis tends to be that there is no difference between the means of the two populations; or, more formally, that the difference is zero (so, for example, that there is no difference between the average heights of two populations of males and females).
Scribbr
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What are null and alternative hypotheses?
May 6, 2022 - It is used in hypothesis testing, with a null hypothesis that the difference in group means is zero and an alternate hypothesis that the difference in group means is different from zero. ... Statistical significance is a term used by researchers to state that it is unlikely their observations could have occurred under the null hypothesis of a statistical test.
Chegg
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Null hypothesis | Chegg Writing
December 14, 2021 - In research, the null hypothesis is the conjecture that states that there is no relationship between the observed variables of a study. In statistics, the null hypothesis is denoted as Ho and is read as H-nought, H-null, or H-zero. Researchers commonly use the null hypothesis to disprove or ...
Itf
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What Is A Null Hypothesis
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Delasign
delasign.com › blog › what-is-a-null-hypothesis
What is a Null Hypothesis?
January 12, 2024 - A null hypothesis, or H0, states that there is no statistical significance between two variables.
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., ...