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Chapter 15-Testing For Differences Between Groups and For Relationships Among Variables TRUE/FALSE 1. Tests are bivariate tests of differences when they involve only two variables: a variable that acts like a dependent variable and a variable that acts as a classification variable. ANS: T PTS: 1 DIF: Moderate REF: p. 384 OBJ: 15-1 NAT: AACSB Reflective Thinking| CB&E Model Research Blooms Knowledge 2. If a researcher is interested in whether adult males purchase a product more frequently than adult females, this is an example of univariate statistics. ANS: F This is an example of bivariate statistics. PTS: 1 DIF: Hard REF: p. 384 OBJ: 15-1 NAT: AACSB Reflective Thinking/ CB&E Model Research Blooms Application 3. The type of measurement, the nature of the comparison, and the number of groups to be compared influence the statistical choice. ANS: T PTS: 1 DIF: Moderate REF: p. 384 OBJ: 15-1 NAT: AACSB Reflective Thinking| CB&E Model Research Blooms Comprehension 4. A cross-tabulation is a simple way to describe the relationships between two groups. ANS: T PTS: 1 DIF: Moderate REF: p. 387 OBJ: 15-2 NAT: AACSB Reflective Thinking| CB&E Model Research Blooms Comprehension 5. One way to test the significance of contingency tables is by means of the t-test. ANS: F One way to test the significance of contingency tables is by means of the chi-square test. PTS: 1 DIF: Moderate REF: p. 387 OBJ: 15-2 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 6. The chi-square test requires the researcher to compare the observed frequencies of the groups with the expected frequencies of the groups. ANS: T PTS: 1 DIF: Moderate REF: p. 387 OBJ: 15-2 NAT: AACSB Reflective Thinking| CB&E Model Research Blooms Comprehension 7. To use the chi-square test, both variables in a 2 x 2 contingency table must be measured on a ratio scale