Procedure Used to Test for Significance

Whenever we perform a significance test, it involves comparing a test value that we have calculated to some critical value for the statistic. It doesn't matter what type of statistic we are calculating (e.g., a t-statistic, a chi-square statistic, an F-statistic, etc.), the procedure to test for significance is the same.
1. Decide on the critical alpha level you will use (i.e., the error rate you are willing to accept).
2. Conduct the research.
3. Calculate the statistic.
4. Compare the statistic to a critical value obtained from a table.
If your statistic is higher than the critical value from the table:
· Your finding is significant.
· You reject the null hypothesis.
· The probability is small that the difference or relationship happened by chance.
If your statistic is lower than the critical value from the table:
· Your finding is not significant.
· You fail to reject the null hypothesis.
· The probability is high that the difference or relationship happened by chance.

Pearson Product-Moment Correlation Coefficient

Table of Critical Values