Course Name: Stats Primer, Section No: 2, Unit No: 33, Unit type: Document
HOW DID WE CALCULATE P VALUE HERE
Hi!
We know from the central limit theorem that the test-statistic variable can be expected to follow a specific distribution such as the Normal or t distribution. If the null hypothesis is true then the exact value of the test-statistic should lie within a certain range known as acceptance region.
The p-value is the probability of observing a more extreme value than that of the test statistic value, provided the null hypothesis is true. In other words, p-value depends on where the test statistic value calculated from the specific sample lies on the distribution given by the null hypothesis.
If the test statistic value is too extreme, then it leads to a p-value smaller than alpha(significance level), leading to the rejection of the null hypothesis.
On the other hand, if the test statistic value is in the acceptance region, then it leads to a p-value larger than alpha, leading to failure of rejection of null hypothesis.