Certified Advanced Alcohol and Drug Counselor (CAADC) Practice Exam

Which statistical method is most appropriate to use when comparing different groups in an experiment?

1. Multiple regression

2. ANOVA

3. Chi-square

4. Solomon four-group design

The correct answer is: ANOVA

ANOVA, or Analysis of Variance, is the statistical method specifically designed for comparing the means of three or more groups in an experiment to determine if there are statistically significant differences among them. This technique is advantageous when the research involves more than two groups, as it helps to assess the influence of one or more independent variables on a dependent variable. In situations where multiple groups are being studied, simply using multiple t-tests to compare each group can inflate the Type I error rate due to numerous comparisons. ANOVA controls for that risk, providing a single test result that indicates whether there are differences in means across the groups. If ANOVA shows significant results, post hoc tests can be employed to identify exactly which groups differ from one another. The other methods mentioned are appropriate for different types of statistical analyses. Multiple regression focuses on understanding the relationship between one dependent variable and one or more independent variables, rather than straightforward group comparisons. The chi-square method is best suited for categorical data to assess whether the distribution of observed frequencies differs from expected frequencies. The Solomon four-group design is a specific experimental design used to control for pretest effects, not a statistical test used for comparison of group means. Thus, ANOVA is the most suitable choice for comparing different groups in an