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50 Hypothesis Testing in Data Analysis - MCQs

This set of 50 MCQs explores key concepts in hypothesis testing, including null and alternative hypotheses, p-values, test statistics, error types, and common tests like t-test, chi-square, and ANOVA. Designed for data analysts and statisticians to reinforce inferential statistics fundamentals.

1. The null hypothesis (H₀) is assumed:

a) True until evidence suggests otherwise
b) False until proven true
c) Equal to the alternative
d) Always contains equality
✅ Correct Answer: a) True until evidence suggests otherwise
📝 Explanation:
Burden of proof lies on rejecting H₀.

2. A Type I error is:

a) Rejecting a true H₀
b) Failing to reject a false H₀
c) Rejecting a false H₀
d) Failing to reject a true H₀
✅ Correct Answer: a) Rejecting a true H₀
📝 Explanation:
False positive; probability = α (significance level).

3. The p-value represents:

a) Probability H₀ is true
b) Probability of data (or more extreme) given H₀
c) Probability H₁ is true
d) 1 – power
✅ Correct Answer: b) Probability of data (or more extreme) given H₀
📝 Explanation:
Small p-value indicates evidence against H₀.

4. For a two-tailed test at α = 0.05, critical z-values are:

a) ±1.645
b) ±1.96
c) ±2.33
d) ±2.58
✅ Correct Answer: b) ±1.96
📝 Explanation:
2.5% in each tail of standard normal.

5. Power of a test is:

a) 1 – β (probability of rejecting false H₀)
b) α
c) p-value
d) 1 – α
✅ Correct Answer: a) 1 – β (probability of rejecting false H₀)
📝 Explanation:
Higher power detects true effects.

6. Increasing sample size generally:

a) Increases power and narrows confidence intervals
b) Decreases power
c) Increases Type I error
d) No effect on power
✅ Correct Answer: a) Increases power and narrows confidence intervals
📝 Explanation:
Standard error decreases as 1/√n.

7. A one-tailed test is appropriate when:

a) Direction of effect is specified in H₁
b) No direction is hypothesized
c) Sample size is small
d) Variance is unknown
✅ Correct Answer: a) Direction of effect is specified in H₁
📝 Explanation:
All α in one tail; more powerful if direction correct.

8. The critical region is the set of test statistic values that lead to:

a) Rejection of H₀
b) Acceptance of H₀
c) p-value calculation
d) Confidence interval
✅ Correct Answer: a) Rejection of H₀
📝 Explanation:
Defined by α and test type.

9. For unknown σ, mean test uses:

a) t-distribution
b) z-distribution
c) Chi-square
d) F-distribution
✅ Correct Answer: a) t-distribution
📝 Explanation:
df = n–1; approaches normal as n grows.

10. In A/B testing, H₀ typically states:

a) No difference in conversion rates (p_A = p_B)
b) Version A is better
c) Sample size is adequate
d) Variance equal
✅ Correct Answer: a) No difference in conversion rates (p_A = p_B)
📝 Explanation:
Rejection suggests statistically significant lift.

11. Effect size measures:

a) Magnitude of difference, independent of sample size
b) Statistical significance
c) p-value
d) Confidence level
✅ Correct Answer: a) Magnitude of difference, independent of sample size
📝 Explanation:
E.g., Cohen’s d, odds ratio.

12. Practical significance differs from statistical significance because:

a) Large n can make tiny effects significant
b) Small n misses large effects
c) Both a and b
d) They are identical
✅ Correct Answer: c) Both a and b
📝 Explanation:
Always report effect size with p-value.

13. The chi-square test for independence requires:

a) Expected frequencies ≥ 5 in most cells
b) Normally distributed data
c) Equal variances
d) Paired observations
✅ Correct Answer: a) Expected frequencies ≥ 5 in most cells
📝 Explanation:
Ensures chi-square approximation validity.

14. Fisher’s exact test is preferred when:

a) Expected cell counts < 5
b) Large contingency tables
c) Continuous data
d) Multiple groups
✅ Correct Answer: a) Expected cell counts < 5
📝 Explanation:
Exact p-value for 2x2 tables.

15. ANOVA tests:

a) Equality of ≥3 population means
b) Two means only
c) Variances
d) Proportions
✅ Correct Answer: a) Equality of ≥3 population means
📝 Explanation:
F = MSB / MSW.

16. Post-hoc tests after ANOVA control:

a) Family-wise error rate (e.g., Tukey, Bonferroni)
b) Type II error
c) Power
d) Effect size
✅ Correct Answer: a) Family-wise error rate (e.g., Tukey, Bonferroni)
📝 Explanation:
Identify which pairs differ.

17. Non-parametric alternative to one-sample t-test:

a) Wilcoxon signed-rank
b) Mann-Whitney U
c) Kruskal-Wallis
d) Sign test
✅ Correct Answer: a) Wilcoxon signed-rank
📝 Explanation:
Tests if median differs from hypothesized value.

18. Mann-Whitney U tests:

a) Difference in distributions of two independent samples
b) Paired data
c) Three or more groups
d) Variance equality
✅ Correct Answer: a) Difference in distributions of two independent samples
📝 Explanation:
Non-parametric two-sample test.

19. The sign test uses:

a) Number of positive/negative differences
b) Ranks
c) Actual values
d) Binomial distribution
✅ Correct Answer: d) Binomial distribution
📝 Explanation:
Simplest non-parametric paired test.

20. Equivalence testing aims to show:

a) Treatments are practically equivalent within margin
b) One is superior
c) No difference
d) Large difference
✅ Correct Answer: a) Treatments are practically equivalent within margin
📝 Explanation:
TOST: two one-sided t-tests.

21. Superiority margin in clinical trials is denoted:

a) δ (non-inferiority if new ≥ old – δ)
b) α
c) β
d) p
✅ Correct Answer: a) δ (non-inferiority if new ≥ old – δ)
📝 Explanation:
Pre-specified clinically meaningful difference.

22. Sequential testing (e.g., alpha spending) allows:

a) Early stopping for efficacy/futility
b) Fixed sample only
c) Post-hoc changes
d) No interim analysis
✅ Correct Answer: a) Early stopping for efficacy/futility
📝 Explanation:
Controls overall Type I error.

23. Multiple testing correction is needed when:

a) Performing many hypothesis tests simultaneously
b) n is small
c) Data are normal
d) Only one test
✅ Correct Answer: a) Performing many hypothesis tests simultaneously
📝 Explanation:
Inflates family-wise error rate.

24. Bonferroni correction adjusts α to:

a) α / m (m = number of tests)
b) α × m
c) α / 2
d) 1 – (1–α)^m
✅ Correct Answer: a) α / m (m = number of tests)
📝 Explanation:
Conservative; controls FWER.

25. False Discovery Rate (FDR) controls:

a) Expected proportion of false positives among rejections
b) Overall Type I error
c) Power
d) Type II error
✅ Correct Answer: a) Expected proportion of false positives among rejections
📝 Explanation:
Benjamini-Hochberg procedure.

26. In z-test for proportions, standard error is:

a) √[p₀(1–p₀)/n]
b) √[p̂(1–p̂)/n]
c) p̂ / √n
d) (p̂ – p₀) / √n
✅ Correct Answer: a) √[p₀(1–p₀)/n]
📝 Explanation:
Under H₀; p₀ is hypothesized proportion.

27. For small n and binary data, use:

a) Binomial test or Fisher’s exact
b) z-test
c) t-test
d) ANOVA
✅ Correct Answer: a) Binomial test or Fisher’s exact
📝 Explanation:
Normal approximation unreliable.

28. The F-test compares:

a) Two population variances
b) Two means
c) Proportions
d) Correlations
✅ Correct Answer: a) Two population variances
📝 Explanation:
H₀: σ₁² = σ₂².

29. Levene’s test is robust to:

a) Non-normality when testing variance equality
b) Small samples
c) Paired data
d) Categorical outcomes
✅ Correct Answer: a) Non-normality when testing variance equality
📝 Explanation:
Uses absolute deviations from median.

30. Paired t-test assumes:

a) Differences are normally distributed
b) Raw observations normal
c) Equal variances
d) Independence
✅ Correct Answer: a) Differences are normally distributed
📝 Explanation:
df = n_pairs – 1.

31. Welch’s t-test adjusts for:

a) Unequal variances in two-sample means
b) Paired data
c) Non-normality
d) Proportions
✅ Correct Answer: a) Unequal variances in two-sample means
📝 Explanation:
Uses Welch-Satterthwaite df.

32. McNemar’s test is for:

a) Paired binary data (before/after)
b) Independent proportions
c) Continuous paired
d) Multiple groups
✅ Correct Answer: a) Paired binary data (before/after)
📝 Explanation:
Focuses on discordant pairs.

33. Cochran’s Q test extends McNemar to:

a) ≥3 related binary samples
b) Independent samples
c) Continuous data
d) Variance
✅ Correct Answer: a) ≥3 related binary samples
📝 Explanation:
Non-parametric repeated measures.

34. The likelihood ratio test compares:

a) Fit of nested models
b) Means
c) Variances
d) Proportions
✅ Correct Answer: a) Fit of nested models
📝 Explanation:
–2(log L_reduced – log L_full) ~ χ².

35. Bayesian hypothesis testing uses:

a) Bayes factor (posterior odds / prior odds)
b) p-value
c) Critical value
d) Confidence interval
✅ Correct Answer: a) Bayes factor (posterior odds / prior odds)
📝 Explanation:
BF > 10 strong evidence for H₁.

36. P-hacking refers to:

a) Manipulating analysis to obtain significant p-value
b) Secure data storage
c) Parallel computing
d) Pre-registration
✅ Correct Answer: a) Manipulating analysis to obtain significant p-value
📝 Explanation:
Undermines scientific integrity.

37. Pre-registration combats p-hacking by:

a) Specifying analysis plan before seeing data
b) Increasing sample size
c) Using non-parametric tests
d) Reporting all tests
✅ Correct Answer: a) Specifying analysis plan before seeing data
📝 Explanation:
Platforms: OSF, ClinicalTrials.gov.

38. Minimum detectable effect (MDE) is:

a) Smallest effect size with desired power
b) Largest effect
c) p-value
d) Sample mean
✅ Correct Answer: a) Smallest effect size with desired power
📝 Explanation:
Used in sample size calculation.

39. Sample size for mean test: n =

a) (z_{α/2} + z_β)² σ² / δ²
b) z² p(1–p) / E²
c) t² s² / d²
d) χ² / df
✅ Correct Answer: a) (z_{α/2} + z_β)² σ² / δ²
📝 Explanation:
δ = effect size; for two-sided.

40. For proportions, n ≈

a) z² [p₁(1–p₁) + p₂(1–p₂)] / (p₁–p₂)²
b) z² p(1–p) / E²
c) Both depending on design
d) t² s / d
✅ Correct Answer: c) Both depending on design
📝 Explanation:
Equal n per group uses pooled variance.

41. Peeking at data mid-trial inflates:

a) Type I error rate
b) Power
c) Effect size
d) Confidence
✅ Correct Answer: a) Type I error rate
📝 Explanation:
Requires alpha-spending functions.

42. O’Brien-Fleming boundary is:

a) Conservative early, liberal later in sequential trials
b) Constant alpha
c) Liberal early
d) No boundary
✅ Correct Answer: a) Conservative early, liberal later in sequential trials
📝 Explanation:
Spends little alpha initially.

43. Cuped (Controlled-experiment Using Pre-experiment Data) reduces variance in A/B tests by:

a) Covariate adjustment with pre-period metric
b) Increasing sample
c) Stratification
d) Blocking
✅ Correct Answer: a) Covariate adjustment with pre-period metric
📝 Explanation:
Y_adj = Y – θ (X_pre – μ_pre).

44. In multi-armed bandit, exploration-exploitation tradeoff is managed by:

a) Thompson sampling, epsilon-greedy
b) Fixed allocation
c) Only best arm
d) Random assignment
✅ Correct Answer: a) Thompson sampling, epsilon-greedy
📝 Explanation:
Adaptive allocation to higher-performing arms.

45. Switchback tests are used in:

a) Time-based interference (e.g., network effects)
b) Independent users
c) Small samples
d) Continuous outcomes only
✅ Correct Answer: a) Time-based interference (e.g., network effects)
📝 Explanation:
Alternate treatment over time periods.

46. The z-test statistic for mean is:

a) (x̄ – μ₀) / (σ/√n)
b) (x̄ – μ₀) / (s/√n)
c) t = (x̄ – μ₀) / (s/√n)
d) (p̂ – p₀) / √[p₀(1–p₀)/n]
✅ Correct Answer: a) (x̄ – μ₀) / (σ/√n)
📝 Explanation:
Known population σ.

47. Confidence interval and hypothesis test are related: if CI excludes μ₀, then:

a) Reject H₀: μ = μ₀ at corresponding α
b) Accept H₀
c) p > α
d) Need larger n
✅ Correct Answer: a) Reject H₀: μ = μ₀ at corresponding α
📝 Explanation:
Duality: 95% CI ↔ two-tailed α=0.05 test.

48. A statistically significant result with p = 0.04 and tiny effect size may indicate:

a) Large sample detecting trivial difference
b) Error in calculation
c) High power
d) Non-normality
✅ Correct Answer: a) Large sample detecting trivial difference
📝 Explanation:
Report confidence interval on effect.

49. Replication crisis highlights importance of:

a) Pre-registration, large n, effect sizes, open data
b) p < 0.05 only
c) Small samples
d) Post-hoc tests
✅ Correct Answer: a) Pre-registration, large n, effect sizes, open data
📝 Explanation:
Improves reproducibility and credibility.

50. The region of practical equivalence (ROPE) in Bayesian testing accepts H₀ if:

a) Posterior credible interval fully within ROPE
b) p < 0.05
c) Bayes factor > 3
d) Prior is vague
✅ Correct Answer: a) Posterior credible interval fully within ROPE
📝 Explanation:
Practical indifference zone around null.
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