Steps for using and
interpreting chi-square
To review, the chi-square method of hypothesis testing has seven basic steps.[1]
1. State the
null and research/alternative hypotheses.
2. Specify the
decision rule and the level of statistical significance for the test, i.e.,
.05, .01, or .001. (A significance
level of .01 would mean that the probability of the chi-square value must be
.01 or less to reject the null hypothesis, a more stringent criterion than
.05.)
3. Compute the
expected values.
4. Compute the
chi-square statistic.
5. Determine the
degrees of freedom for the table. Then
identify the critical value of chi-square at the specified level of
significance and appropriate degrees of freedom.
6. Compare the computed chi-square statistic with the
critical value of chi-square; reject
the null hypothesis if the chi-square is equal to or larger than the critical
value; accept the null hypothesis if
the chi-square is less than the critical value.
7. State a substantive conclusion, i.e., describe the meaning and importance of the test results in terms of the historical problem under investigation.
[1] Based on the discussion in Robert M. Schwartz, History and Statistics: The Case of Witchcraft in Early Modern Europe and New England (New York: NLA Monograph Series, 1992).