Statistics Quiz: Can You Master Hypothesis Testing & P-values?

1. A test yields a p-value of 0.15 with α = 0.05. Which conclusion is correct?

The null hypothesis is definitely true

There is insufficient evidence to reject the null hypothesis

The alternative hypothesis is false

The sample size was too small

2. True or False: A 95% confidence level corresponds to α = 0.05.

True

False

3. True or False: Type II error is the probability of rejecting a true null hypothesis.

True

False

4. True or False: Increasing sample size generally increases statistical power.

True

False

5. True or False: A p-value of 0.04 proves that the null hypothesis is false.

True

False

Submit

10. What is the critical value in hypothesis testing?

The p-value that equals the test statistic

The boundary value that separates the rejection region from the non-rejection region

The minimum acceptable sample mean

The standard deviation of the population

11. What is the null hypothesis typically designed to represent?

A statement of no effect or no difference

The expected research outcome

The most likely population parameter

An alternative explanation for data variation

12. If a p-value is less than the significance level, what decision should be made?

Fail to reject the null hypothesis

Reject the null hypothesis

Accept the null hypothesis as proven

Collect more data before deciding

13. Which factors increase statistical power? Select all that apply.

Larger sample size

Larger effect size

Lower significance level

Smaller standard deviation

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14. What does statistical power represent?

The probability of Type I error

The probability of correctly rejecting a false null hypothesis

The strength of the sample correlation

The ability to detect a small effect size

15. In a two-tailed hypothesis test with α = 0.05, how is the critical region divided?

0.05 in one tail only

0.025 in each tail

0.05 split equally across both tails

Entirely in the left tail

16. A researcher uses α = 0.05. What does this mean?

There is a 5% chance of Type II error

The researcher is willing to accept a 5% risk of rejecting a true null hypothesis

The sample size must be at least 5% of the population

Results are significant if they fall within the middle 5% of the distribution

17. Which statement correctly describes a Type II error?

Incorrectly rejecting the null hypothesis

Failing to reject a false null hypothesis

Using a sample that is too small

Selecting the wrong test statistic

18. What is the relationship between significance level (α) and Type I error?

The significance level equals the probability of Type I error

Type I error increases as α decreases

They are unrelated concepts

Significance level determines power, not Type I error

19. In hypothesis testing, what is a Type I error?

Failing to reject a false null hypothesis

Rejecting a true null hypothesis

Using an inappropriate sample size

Misinterpreting the alternative hypothesis

20. A p-value of 0.03 in a hypothesis test means what?

The null hypothesis is true 3% of the time

There is a 3% probability of observing this data if the null hypothesis is true

The alternative hypothesis is 97% likely to be correct

The sample mean differs from the population mean by 3%

Statistics Quiz: Can You Master Hypothesis Testing & p-values?

1. A test yields a p-value of 0.15 with α = 0.05. Which conclusion is correct?

2.

What first name or nickname would you like us to use?

2. True or False: A 95% confidence level corresponds to α = 0.05.

3. True or False: Type II error is the probability of rejecting a true null hypothesis.

4. True or False: Increasing sample size generally increases statistical power.

5. True or False: A p-value of 0.04 proves that the null hypothesis is false.

6. A smaller p-value indicates stronger evidence ____ the null hypothesis.

7. Statistical Methods (Data+) rely on ____ to determine whether observed differences are due to chance.

8. The ____ hypothesis states that there is a significant difference or effect.

9. In a one-sample t-test, the test statistic is calculated as ____.

10. What is the critical value in hypothesis testing?

11. What is the null hypothesis typically designed to represent?

12. If a p-value is less than the significance level, what decision should be made?

13. Which factors increase statistical power? Select all that apply.

14. What does statistical power represent?

15. In a two-tailed hypothesis test with α = 0.05, how is the critical region divided?

16. A researcher uses α = 0.05. What does this mean?

17. Which statement correctly describes a Type II error?

18. What is the relationship between significance level (α) and Type I error?

19. In hypothesis testing, what is a Type I error?

20. A p-value of 0.03 in a hypothesis test means what?