explain what a p-value is. what is the criterion for rejecting the null hypothesis using the p-value approach?
What is a p-value and what is the criterion for rejecting the null hypothesis using the p-value approach?
Answer:
A p-value is a statistical measure that helps determine the strength of the evidence against the null hypothesis. It quantifies the probability of obtaining results as extreme as the observed results of a statistical hypothesis test, assuming that the null hypothesis is true.
The criterion for rejecting the null hypothesis using the p-value approach is as follows:
- If the p-value is less than or equal to the significance level (often denoted as α, typically 0.05), then there is enough evidence to reject the null hypothesis.
- Conversely, if the p-value is greater than the significance level, there is not enough evidence to reject the null hypothesis.
In simpler terms, a smaller p-value indicates stronger evidence against the null hypothesis, leading to its rejection. Researchers commonly use a significance level of 0.05, which means that in order to reject the null hypothesis, the p-value must be less than 0.05. This approach helps researchers make informed decisions based on the likelihood of obtaining the observed results if the null hypothesis were true.