1. What is the primary advantage of using parametric tests over nonparametric tests in statistical analysis? - A) They require less data - B) They are less complex - C) They can provide more powerful and precise estimates - D) They do not assume underlying data distribution Answer: C) They can provide more powerful and precise estimates Rationale: Parametric tests are based on assumptions about the data's distribution and often have more statistical power than non-parametric tests, allowing for more precise estimates. 2. In a clinical trial comparing blood pressure levels before and after a new medication, which parametric test would be most appropriate? - A) Chi-square test - B) T-test for independent samples - C) T-test for paired samples - D) ANOVA Answer: C) T-test for paired samples Rationale: A t-test for paired samples is used when comparing two related groups, such as the same group of patients' blood pressure before and after treatment. 3. When is it appropriate to use an ANOVA test in healthcare research? - A) When comparing categorical data across multiple groups - B) When comparing the means of two groups - C) When comparing the means of three or more groups - D) When analyzing ordinal data Answer: C) When comparing the means of three or more groups Rationale: ANOVA is used to compare the means across three or more groups to determine if at least one group mean is statistically different from the others. 4. What assumption must be met to properly conduct a Pearson's correlation analysis? - A) The relationship between variables is non-linear - B) Variables are measured on an ordinal scale - C) Homogeneity of variance