,NURS 5366 Module 4 Quiz | Principles of Research in
Nursing (2026) Q&A | UTA
1. A researcher wants to determine if a new teaching method improves student test
scores. The null hypothesis states that there is no difference in test scores between
the traditional and new teaching methods. If the researcher rejects the null
hypothesis when it is actually true, what type of error has occurred?
A) Type I error
B) Type II error
C) Sampling error
D) Measurement error
Correct Answer: A) Type I error
Rationale: A Type I error, also known as alpha error, occurs when the null hypothesis
is rejected when it is actually true. This is a false positive result. A Type II error (beta
error) occurs when the null hypothesis is not rejected when it is actually false.
2. Which of the following best describes the relationship between sample size and
statistical power?
A) As sample size increases, statistical power decreases.
B) As sample size increases, statistical power increases.
C) Sample size has no effect on statistical power.
D) Statistical power is only affected by the alpha level, not sample size.
Correct Answer: B) As sample size increases, statistical power increases.
,Rationale: Statistical power is the probability of correctly rejecting a false null
hypothesis (1 - beta). Larger sample sizes reduce sampling error and increase the
ability to detect a true effect, thereby increasing statistical power. Smaller sample
sizes have less power and are more likely to commit a Type II error.
3. Which statistical test is most appropriate for comparing the means of two
independent groups when the data are normally distributed and the variances are
equal?
A) Mann-Whitney U test
B) Paired t-test
C) Independent samples t-test
D) Chi-square test
Correct Answer: C) Independent samples t-test
Rationale: The independent samples t-test is a parametric test used to compare the
means of two independent groups when the data are normally distributed and
variances are equal. The Mann-Whitney U test is the non-parametric alternative. The
paired t-test is used for dependent groups, and the chi-square test is used for
categorical data.
4. A researcher calculates a 95% confidence interval for the mean difference between
two groups as 2.5 to 7.5. What is the correct interpretation of this confidence
interval?
A) There is a 95% probability that the true mean difference lies between 2.5 and 7.5.
B) The probability that the null hypothesis is true is 5%.
C) If the study were repeated many times, 95% of the calculated confidence intervals
would contain the true mean difference.
D) There is a 95% chance that the sample mean difference is between 2.5 and 7.5.
, Correct Answer: C) If the study were repeated many times, 95% of the calculated
confidence intervals would contain the true mean difference.
Rationale: A 95% confidence interval means that if the same study were repeated
many times, 95% of the intervals calculated from those samples would contain the
true population parameter. It is not a probability statement about the current interval
or the null hypothesis.
5. A researcher conducts a study with an alpha level of 0.05 and obtains a p-value of
0.03. What is the most appropriate conclusion?
A) Fail to reject the null hypothesis; the results are not statistically significant.
B) Reject the null hypothesis; the results are statistically significant.
C) Reject the null hypothesis; the results are clinically significant.
D) Fail to reject the null hypothesis; the results are clinically significant.
Correct Answer: B) Reject the null hypothesis; the results are statistically significant.
Rationale: A p-value of 0.03 is less than the alpha level of 0.05, indicating that the
results are statistically significant. The null hypothesis should be rejected. Statistical
significance does not automatically imply clinical significance.
6. What is the primary purpose of hypothesis testing in research?
A) To prove that the research hypothesis is correct
B) To determine the probability that the research findings are due to chance
C) To establish the clinical significance of the findings
D) To determine the sample size
Correct Answer: B) To determine the probability that the research findings are due
to chance
Nursing (2026) Q&A | UTA
1. A researcher wants to determine if a new teaching method improves student test
scores. The null hypothesis states that there is no difference in test scores between
the traditional and new teaching methods. If the researcher rejects the null
hypothesis when it is actually true, what type of error has occurred?
A) Type I error
B) Type II error
C) Sampling error
D) Measurement error
Correct Answer: A) Type I error
Rationale: A Type I error, also known as alpha error, occurs when the null hypothesis
is rejected when it is actually true. This is a false positive result. A Type II error (beta
error) occurs when the null hypothesis is not rejected when it is actually false.
2. Which of the following best describes the relationship between sample size and
statistical power?
A) As sample size increases, statistical power decreases.
B) As sample size increases, statistical power increases.
C) Sample size has no effect on statistical power.
D) Statistical power is only affected by the alpha level, not sample size.
Correct Answer: B) As sample size increases, statistical power increases.
,Rationale: Statistical power is the probability of correctly rejecting a false null
hypothesis (1 - beta). Larger sample sizes reduce sampling error and increase the
ability to detect a true effect, thereby increasing statistical power. Smaller sample
sizes have less power and are more likely to commit a Type II error.
3. Which statistical test is most appropriate for comparing the means of two
independent groups when the data are normally distributed and the variances are
equal?
A) Mann-Whitney U test
B) Paired t-test
C) Independent samples t-test
D) Chi-square test
Correct Answer: C) Independent samples t-test
Rationale: The independent samples t-test is a parametric test used to compare the
means of two independent groups when the data are normally distributed and
variances are equal. The Mann-Whitney U test is the non-parametric alternative. The
paired t-test is used for dependent groups, and the chi-square test is used for
categorical data.
4. A researcher calculates a 95% confidence interval for the mean difference between
two groups as 2.5 to 7.5. What is the correct interpretation of this confidence
interval?
A) There is a 95% probability that the true mean difference lies between 2.5 and 7.5.
B) The probability that the null hypothesis is true is 5%.
C) If the study were repeated many times, 95% of the calculated confidence intervals
would contain the true mean difference.
D) There is a 95% chance that the sample mean difference is between 2.5 and 7.5.
, Correct Answer: C) If the study were repeated many times, 95% of the calculated
confidence intervals would contain the true mean difference.
Rationale: A 95% confidence interval means that if the same study were repeated
many times, 95% of the intervals calculated from those samples would contain the
true population parameter. It is not a probability statement about the current interval
or the null hypothesis.
5. A researcher conducts a study with an alpha level of 0.05 and obtains a p-value of
0.03. What is the most appropriate conclusion?
A) Fail to reject the null hypothesis; the results are not statistically significant.
B) Reject the null hypothesis; the results are statistically significant.
C) Reject the null hypothesis; the results are clinically significant.
D) Fail to reject the null hypothesis; the results are clinically significant.
Correct Answer: B) Reject the null hypothesis; the results are statistically significant.
Rationale: A p-value of 0.03 is less than the alpha level of 0.05, indicating that the
results are statistically significant. The null hypothesis should be rejected. Statistical
significance does not automatically imply clinical significance.
6. What is the primary purpose of hypothesis testing in research?
A) To prove that the research hypothesis is correct
B) To determine the probability that the research findings are due to chance
C) To establish the clinical significance of the findings
D) To determine the sample size
Correct Answer: B) To determine the probability that the research findings are due
to chance
