Significance tests and their types MCQs With Answer

Introduction: This quiz collection on Significance tests and their types is designed for M.Pharm students to strengthen their understanding of hypothesis testing, selection of appropriate tests, underlying assumptions, and interpretation of results. The questions focus on common parametric and nonparametric methods used in pharmaceutical research, clinical trials, and laboratory studies — including t-tests, ANOVA, chi-square, Mann–Whitney, Wilcoxon, Kruskal–Wallis, and post-hoc procedures. Emphasis is placed on when to use each test, assumptions like normality and homogeneity of variance, effect size and power considerations, and practical scenarios encountered in drug development and bioequivalence studies. Use this set to assess and deepen your applied biostatistics skills.

Q1. Which test is most appropriate when comparing the means of two independent groups with small sample sizes and unknown population standard deviation?

• Two-sample z-test
• Independent (unpaired) t-test
• Mann–Whitney U test
• Paired t-test

Correct Answer: Independent (unpaired) t-test

Q2. If the outcome variable is ordinal or continuous but not normally distributed and you need to compare two independent groups, which test should you use?

• Paired t-test
• Mann–Whitney U test
• One-way ANOVA
• Chi-square test

Correct Answer: Mann–Whitney U test

Q3. Which significance test is suitable for comparing proportions between two independent categorical groups when expected cell counts are small (e.g., <5)?

• Chi-square test (Pearson)
• Fisher’s exact test
• Z-test for proportions
• McNemar test

Correct Answer: Fisher’s exact test

Q4. What is the nonparametric equivalent of one-way ANOVA for comparing more than two independent groups?

• Kruskal–Wallis test
• Friedman test
• Mann–Whitney U test
• Wilcoxon signed-rank test

Correct Answer: Kruskal–Wallis test

Q5. Which test assesses whether paired categorical data (before-and-after binary outcomes) show a significant change?

• Chi-square test for independence
• McNemar test
• Paired t-test
• Fisher’s exact test

Correct Answer: McNemar test

Q6. When comparing the means of three or more independent groups under parametric assumptions, which test is commonly used?

• One-way ANOVA
• Kruskal–Wallis test
• Repeated measures ANOVA
• Wilcoxon signed-rank test

Correct Answer: One-way ANOVA

Q7. If variances between two groups are unequal, which version of the t-test is preferable?

• Pooled two-sample t-test
• Welch’s t-test
• One-sample t-test
• Paired t-test

Correct Answer: Welch’s t-test

Q8. Which test is designed to compare paired continuous measurements from the same subjects (e.g., pre- and post-treatment) when normality holds?

• Independent t-test
• Paired t-test
• Mann–Whitney U test
• Chi-square test

Correct Answer: Paired t-test

Q9. What does a p-value represent in the context of a significance test?

• The probability that the null hypothesis is true
• The probability of observing data as extreme as or more extreme than the sample, assuming the null hypothesis is true
• The effect size of the treatment
• The Type II error rate (beta)

Correct Answer: The probability of observing data as extreme as or more extreme than the sample, assuming the null hypothesis is true

Q10. Which test is appropriate for checking normality of a continuous variable in a small to moderate sample size?

• Levene’s test
• Shapiro–Wilk test
• Kruskal–Wallis test
• Kolmogorov–Smirnov with Lilliefors correction

Correct Answer: Shapiro–Wilk test

Q11. For comparing survival distributions between two groups, which significance test is commonly used?

• Log-rank test
• Student’s t-test
• Chi-square test
• Wilcoxon rank-sum test

Correct Answer: Log-rank test

Q12. Which post-hoc test controls the family-wise error rate after a significant one-way ANOVA and is conservative for unequal sample sizes?

• Tukey’s Honestly Significant Difference (HSD)
• Bonferroni correction
• Dunnett’s test
• Scheffé’s method

Correct Answer: Scheffé’s method

Q13. What is the primary purpose of a two-tailed test compared to a one-tailed test?

• To test for difference in a specific direction only
• To test for any difference regardless of direction
• To increase statistical power for directional hypotheses
• To adjust significance level automatically

Correct Answer: To test for any difference regardless of direction

Q14. Which test evaluates whether two continuous variables have a linear relationship assuming bivariate normality?

• Spearman rank correlation
• Pearson correlation coefficient
• Chi-square test
• Kendall’s tau

Correct Answer: Pearson correlation coefficient

Q15. When analyzing variance components or comparing variances between two normal populations, which test is employed?

• F-test for equality of variances
• Levene’s test
• Bartlett’s test
• Welch’s t-test

Correct Answer: F-test for equality of variances

Q16. In crossover bioequivalence studies, which test is commonly used to analyze paired continuous pharmacokinetic measures?

• Independent t-test
• Paired t-test or mixed-effects model depending on design
• Mann–Whitney U test
• Chi-square test

Correct Answer: Paired t-test or mixed-effects model depending on design

Q17. Which nonparametric test is suitable for comparing more than two related (paired) samples, such as repeated measures on the same subjects?

• Kruskal–Wallis test
• Friedman test
• Repeated measures ANOVA
• Wilcoxon rank-sum test

Correct Answer: Friedman test

Q18. What does statistical power (1 − β) represent in hypothesis testing?

• The probability of incorrectly rejecting the null hypothesis
• The probability of correctly accepting the null hypothesis
• The probability of correctly rejecting the null hypothesis when the alternative is true
• The significance level chosen by the investigator

Correct Answer: The probability of correctly rejecting the null hypothesis when the alternative is true

Q19. When analyzing contingency tables larger than 2×2, which test assesses association while approximating the sampling distribution with chi-square under large-sample conditions?

• Fisher’s exact test
• Pearson chi-square test
• McNemar test
• Wilcoxon signed-rank test

Correct Answer: Pearson chi-square test

Q20. Which modern approach can be used to assess significance without strict distributional assumptions by resampling the observed data?

• Bayesian inference
• Bootstrap or permutation tests
• Student’s t-test
• ANOVA with Greenhouse–Geisser correction

Correct Answer: Bootstrap or permutation tests

Download