Null hypothesis: Difference between revisions
CSV import Tags: mobile edit mobile web edit |
CSV import Tag: Reverted |
||
| Line 30: | Line 30: | ||
{{stub}} | {{stub}} | ||
{{No image}} | {{No image}} | ||
__NOINDEX__ | |||
Revision as of 21:22, 17 March 2025
Null Hypothesis is a fundamental concept in Statistics that refers to a general statement or default position that there is no relationship between two measured phenomena, or no association among groups. It is often denoted as H0.
Overview
The null hypothesis is a starting point in Statistical hypothesis testing, a method of inference used in statistics. The testing process involves stating a null and alternative hypothesis, collecting data, and then testing the null hypothesis. If the data strongly contradicts the null hypothesis, then it is rejected in favor of the Alternative hypothesis.
History
The concept of the null hypothesis was first proposed by Ronald Fisher, a British statistician and geneticist, in the early 20th century. Fisher introduced the idea as a part of his development of Statistical tests.
Formulation
The null hypothesis is typically a hypothesis of no difference or no effect. For example, if testing the effect of a drug, the null hypothesis might be that the drug has no effect on a disease. The alternative hypothesis, on the other hand, might be that the drug does have an effect.
Testing
Testing the null hypothesis involves collecting data and calculating a Test statistic. The test statistic is then compared to a critical value, which is determined based on the Significance level chosen for the test. If the test statistic is more extreme than the critical value, the null hypothesis is rejected.
Criticisms
Despite its widespread use, the null hypothesis has been criticized. Some critics argue that it is often misused or misunderstood, while others argue that it is inherently flawed and should be replaced with other methods of statistical inference.
See also
References
<references />


