We want to know if a nurse’s perception of EBP depends on their organizational level. A chi-square test is the appropriate method for comparing two nominal or ordinal variables. The null hypothesis for this test is that perception is independent of organization level. The alternative hypothesis is that perception depends on organization level.

If the null hypothesis is true, that there is no difference in perception by organization level, then we would expect to see the same proportion in each rating category for both the nurse professionals and the nurse leaders. If the proportions are not close between the nurse professionals and the nurse leaders, we would suspect that their perceptions of EBP differ. As with other hypothesis tests, we need to ascertain that the differences we see are statistically significant and not due to sampling error. We will use a chi-square test statistic. This measures the discrepancy between the frequencies we observed in our sample and what we would expect under the null hypothesis. The chi-square test statistic follows a chi-square distribution.

When comparing two nominal/ordinal variables, it is customary to present the data in a contingency table. In our case, we have two organization levels and five response levels, so our contingency table will have two rows and five columns. Each “cell” of the table contains the frequency for each combination of organization and response level. An important assumption in conducting a chi-square test for independence is that no more than 20% of the cells can have expected frequencies of five or less. We also assume that the survey responses are independent. The chi-square test concerns the independence of the two factors – organization level and perception. The assumption of independence has to do with how the data was collected, i.e., a participant’s response is not influenced or related to the response of another participant.