LOS F requires us to:
explain and interpret the p-value as it relates to hypothesis testing
a. P-value is the smallest level of significance at which a given null hypothesis can be rejected.
b. Smaller the P-value, the stronger the evidence. Lower levels lead to greater confidence but come at an increased risk of Type II errors.
c. It is the output of statistical software such as SPSS, SAS, etc.
d. For a given test statistic and its distribution, we can determine the lowest possible level of alpha (highest possible critical value) for which we would reject the null hypothesis.
i. Calculate the test statistic as before.
ii. Use a statistical package, spreadsheet, etc., to look up the “inverse” value of that test statistic.
iii. This value is the probability at which you would encounter a test statistic of that magnitude or greater (lesser).