A.
Statistical significance always implies clinical significance.
✓
B.
Statistical significance does not always imply clinical significance.
✓
C.
The study had too many participants.
✓
D.
The p-value is too low.
✓
A.
Simple linear regression.
✓
B.
Multiple linear regression.
✓
C.
Logistic regression.
✓
A.
Descriptive statistics.
✓
B.
Inferential statistics.
✓
A.
Independent samples t-test.
✓
C.
Chi-square test of independence.
✓
A.
The p-value is too high.
✓
B.
The study had too much power.
✓
C.
Loss to follow-up can introduce bias and threaten the internal validity of the study.
✓
D.
The drug is definitely effective.
✓
A.
To immediately impute all missing values.
✓
B.
To investigate the pattern of missingness and assess its potential impact on bias and the validity of results.
✓
C.
To ignore the missing values if they are less than 5%.
✓
D.
To discard all records with missing values.
✓
A.
Reject the null hypothesis.
✓
B.
Fail to reject the null hypothesis.
✓
C.
Accept the alternative hypothesis.
✓
D.
The result is statistically significant.
✓
A.
A smaller sample size will be needed.
✓
B.
A larger sample size will be needed to detect a statistically significant difference.
✓
C.
The standard deviation is irrelevant to sample size.
✓
D.
The study should be abandoned.
✓
B.
Independent samples t-test.
✓
C.
Pearson correlation.
✓
A.
Binomial distribution.
✓
B.
Poisson distribution.
✓
C.
Normal distribution, regardless of the population distribution.
✓
D.
Uniform distribution.
✓
A.
Independent samples t-test.
✓
C.
Chi-square test of independence.
✓
D.
Survival analysis (e.g., Kaplan-Meier or Cox regression).
✓
A.
The probability of making a Type II error.
✓
B.
The probability of correctly rejecting the null hypothesis.
✓
C.
The maximum acceptable probability of making a Type I error (false positive).
✓
D.
The power of the test.
✓
A.
To immediately accept the findings.
✓
B.
To critically evaluate the potential for selection bias and its impact on the validity of the results.
✓
C.
To ignore the methods and focus only on the p-value.
✓
D.
To ask the researchers to collect more data.
✓
A.
Independent samples t-test.
✓
C.
Chi-square test of independence.
✓
