Chapter 15—Testing for Differences Between Groups and for Predictive Relationships
TRUE/FALSE
1. Cross-tabulation tables typically provide an easy, intuitive way of understanding data.
2. When the difference between two groups is measured, bivariate statistics are used.
3. If a researcher is interested in whether adult males purchase a product more frequently than adult
females, univariate statistics would be used in the analysis of data.
4. One way to test the significance of the relationship shown in a contingency tables is by means of the
chi-square test.
5. The chi-square test involves comparison of the observed frequencies of the groups with the expected
frequencies of the groups.
6. The chi-square test tests the significance of the relationship shown in an R X C contingency table in
which R stands for row and C stands for column.
7. To use the chi-square test, both variables in a 2 x 2 contingency table must be measured on a ratio
scale.
8. The chi-square test requires that the expected frequency in each cell of the contingency table be at least
30.