Accept
Definition
In statistical inference, we never truly accept either the null or alternative hypotheses. Instead, based on our analysis, we either have enough evidence to reject (disprove) the null hypothesis or fail to reject it.
Analogy
Think of accepting the null hypothesis as similar to a detective closing a case due to lack of evidence. They don't confirm the person's innocence, but rather state that there is not enough evidence to prove their guilt.
Related terms
Significance Level: The predetermined threshold used in hypothesis testing to determine whether we have enough evidence to reject the null hypothesis.
Confidence Interval: A range of values within which we estimate that a parameter lies with a certain level of confidence.
Statistical Power: The probability of correctly rejecting the null hypothesis when it is false, i.e., detecting a true effect or relationship.
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