MCQ on t Test with Answers (Advanced Questions)

T Test MCQs with Answer: A t-test is a statistical method used to determine whether there is a significant difference between the means of two groups. It’s commonly used when the sample size is small (usually n < 30) and the population variance is unknown. The t-test compares the observed difference in sample means to what would be expected by chance. There are different types of t-tests: the independent t-test compares means from two different groups, the paired t-test compares means from the same group at different times, and the one-sample t-test compares the sample mean to a known value. If the t-value exceeds a critical value, the null hypothesis is rejected, suggesting a significant difference. This is an advanced (PG Level) MCQ on t Test (Student’s t Test) with answer key and explanations. You can download the MCQ as PDF from the download link provided below the quiz result page.

Biostatistics Notes  |  Biostatistics PPTs  |  Biostatistics MCQs

1. 
Which of the following scenarios is most appropriate for using an independent samples t-test?

2. 
What assumption must be met for the t-test to be valid?

3. 
What does the t-statistic represent in a t-test?

4. 
In a paired samples t-test, what are we primarily interested in comparing?

5. 
Which of the following describes the null hypothesis in a t-test?

6. 
If you conduct a one-sample t-test with a sample mean of 100, a population mean of 95, a standard deviation of 10, and a sample size of 25, what is the t-statistic?

7. 
How does the shape of the t-distribution compare to the normal distribution as the sample size increases?

8. 
When should a two-tailed t-test be used instead of a one-tailed t-test?

9. 
What is the primary purpose of the Welch’s t-test?

10. 
Which of the following increases the power of a t-test?

11. 
If the p-value obtained from a t-test is 0.03, and the significance level (alpha) is 0.05, what is the appropriate conclusion?

12. 
What is the effect of increasing sample size on the t-statistic in a t-test?

13. 
If a researcher uses a one-sample t-test to compare the sample mean to a known population mean, what is the degrees of freedom for the test?

14. 
What would be the impact of using a non-parametric test instead of a t-test when the data is not normally distributed?

15. 
In the context of a t-test, what is "effect size" typically used to measure?

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