statistical concept
Wikipedia
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Null hypothesis - Wikipedia
3 weeks ago - {\textstyle H_{0}} ) is the claim in scientific research that the effect being studied does not exist. The null hypothesis can also be described as the hypothesis in which no relationship exists between two sets of data or variables being analyzed. If the null hypothesis is true, any experimentally ...
National University
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Null & Alternative Hypotheses - Statistics Resources - LibGuides at National University
Alternative Hypothesis (Ha) – This is also known as the claim. This hypothesis should state what you expect the data to show, based on your research on the topic. This is your answer to your research question. ... Null Hypothesis: H0: There is no difference in the salary of factory workers based on gender.
Videos
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Hypothesis Testing and The Null Hypothesis - YouTube
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The Null Hypothesis and Research Hypothesis - YouTube
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What is a Null Hypothesis? (4 Minute Easy Explanation) - YouTube
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What's a null hypothesis? // How to write a null hypothesis - YouTube
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Null hypothesis explained - 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.
scribbr.com
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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.
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Null & Alternative Hypotheses | Definitions, Templates & Examples
Scribbr
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Null & Alternative Hypotheses | Definitions, Templates & Examples
January 24, 2025 - A null hypothesis claims that there is no effect in the population, while an alternative hypothesis claims that there is an effect.
iSixSigma
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Null Hypothesis vs. Hypothesis: What's the Difference? - isixsigma.com
The second is called the dependent variable, which is the measurable result. However, the biggest difference between the two is that a null hypothesis cannot be proven; it can only be rejected.
Published February 4, 2025
Investopedia
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Null Hypothesis: What Is It and How Is It Used in Investing?
May 8, 2025 - 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.
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 - Null hypothesis testing is a formal approach to deciding between two interpretations of a statistical relationship in a sample. 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.
Reddit
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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.
Statistics Solutions
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Null hypothesis and Alternative Hypothesis - Statistics Solutions
May 14, 2025 - 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. You should express them as simply and concisely as possible.
Statistics By Jim
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Null Hypothesis: Definition, Rejecting & Examples - Statistics By Jim
November 7, 2022 - It is one of two mutually exclusive hypotheses about a population in a hypothesis test. When your sample contains sufficient evidence, you can reject the null and conclude that the effect is statistically significant.
PubMed
pubmed.ncbi.nlm.nih.gov › 8900794
Hypothesis testing - PubMed
Hypothesis testing is the process of making a choice between two conflicting hypotheses. The null hypothesis, H0, is a statistical proposition stating that there is no significant difference between a hypothesized value of a population parameter and its value estimated from a sample drawn from that population.
BYJUS
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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.
Lumen Learning
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Null and Alternative Hypotheses | Introduction to Statistics
If certain conditions about the sample are satisfied, then the claim can be evaluated for a population. In a hypothesis test, we: Evaluate the null hypothesis, typically denoted with H0. The null is not rejected unless the hypothesis test shows otherwise.
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.2 This assessment is critical for scientific inference; if the observed findings are unlikely to be from chance alone, then the scientist should reject the null hypothesis in favor of a feasible alternative.
PubMed Central
pmc.ncbi.nlm.nih.gov › articles › PMC6785820
An Introduction to Statistics: Understanding Hypothesis Testing and Statistical Errors - PMC
In statistical terms, this belief or assumption is known as a hypothesis. Counterintuitively, what the researcher believes in (or is trying to prove) is called the “alternate” hypothesis, and the opposite is called the “null” hypothesis; every study has a null hypothesis and an alternate ...
Crafton Hills College
craftonhills.edu › current-students › tutoring-center › mathematics-tutoring › null_hypothesis_vs_alternative_hypothesis.pdf pdf
How to Identify the Null Hypothesis vs. the Alternative Hypothesis
How to Identify the Null Hypothesis · vs. the Alternative Hypothesis · The Null Hypothesis (Ho): The Alternative Hypothesis (Ha): Contains a statement of equality: The complement of the null hypothesis, which · contains a statement of strict inequality: Mathematical ·
Quora
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What is the difference between a hypothesis and a null hypothesis? - Quora
Answer (1 of 8): A hypothesis is a proposed reason why something happened. For every hypothesis there is a null hypothesis: “Nope, that’s not the reason.” If your hypothesis is wrong, then any correlations or connections between the reason ...
Statistics How To
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Null Hypothesis Definition and Examples, How to State - Statistics How To
October 6, 2024 - The null hypothesis, H0 is the commonly accepted fact; it is the opposite of the alternate hypothesis. Researchers work to reject, nullify or disprove the null hypothesis. Researchers come up with an alternate hypothesis, one that they think explains a phenomenon, and then work to reject the null hypothesis.
Biology Online
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Null hypothesis - Definition and Examples - Biology Online Dictionary
June 16, 2022 - Thus, a null hypothesis is a hypothesis that is valid or presumed true until invalidated by a statistical test. And so, one cannot say that a null hypothesis is ‘’accepted’’ rather it “cannot be rejected” as it remains to be true based on the statistical evidence supporting it.
Tallahassee State College
tsc.fl.edu › media › divisions › learning-commons › resources-by-subject › math › statistics › The-Null-and-the-Alternative-Hypotheses.pdf pdf
The Null and the Alternative Hypotheses
more than or less than 50%. The Null and Alternative Hypotheses looks like: H0: p = 0.5 (This is ... They want to test what proportion of the parts do not meet the specifications. Since they claim · that the proportion is less than 2%, the symbol for the Alternative Hypothesis will be <. As is the