A statement that a parameter has a certain value, written as H(0)
Null hypothesis
When conducting hypothesis testing, the null hypothesis (H0) represents the hypothesis of no effect or no difference between groups. The statement H(0) refers to the value of a parameter (such as a mean, proportion, or standard deviation) assumed under the null hypothesis.
For example, if we were testing whether a new medication was effective in reducing high blood pressure, the null hypothesis might be there is no difference in blood pressure levels between the group that receives the medication and the group that receives a placebo. In this case, H(0) would represent the mean difference in blood pressure levels between the two groups, assuming no effect of the medication.
This value is important because we use it to calculate the test statistic and determine whether the observed data provides enough evidence to reject the null hypothesis. If the observed data produces a test statistic that is unlikely to occur under the null hypothesis (i.e. a p-value below a predetermined significance level), we reject H(0) and conclude that there is sufficient evidence to support the alternative hypothesis. If the p-value is above our significance level, we fail to reject H(0) and conclude that there is not enough evidence to support the alternative hypothesis.
More Answers:
P-Values: Calculating The Evidence Against Null Hypothesis And For Alternative HypothesisHypothesis Testing: Comparing Sample Values To Critical Values In T-Tests And Chi-Squared Tests
A Step-By-Step Guide To Hypothesis Testing In Inferential Statistics