Data+ Hypothesis Testing Fundamentals Quiz

1. What is the alternative hypothesis (H₁) in a two-tailed test for comparing two means?

μ₁ = μ₂

μ₁ ≠ μ₂

μ₁ > μ₂

μ₁ < μ₂

2. True or False: Rejecting the null hypothesis proves that the alternative hypothesis is true.

True

False

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4. Which condition violates the assumption of independence in a paired t-test?

Observations within pairs are correlated with each other

The paired observations come from the same subject or matched pair

The sample size is too large

The data is normally distributed

5. True or False: The significance level α is the same as the p-value.

True

False

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7. A p-value of 0.001 is compared to α = 0.05. What is the correct decision?

Fail to reject H₀; no significant evidence

Reject H₀; significant evidence at the 0.05 level

Accept H₀ as true

Increase the sample size

8. When comparing categorical variables across groups, which test is appropriate?

One-sample t-test

Chi-square test of independence

Pearson correlation

Linear regression

9. True or False: A hypothesis test with a larger sample size generally has greater statistical power.

True

False

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11. In hypothesis testing, the null hypothesis (H₀) represents what assumption?

The effect or difference we expect to find

No effect or no difference exists in the population

The sample is representative of the population

The alternative hypothesis is false

12. Which test would you use to compare the means of two independent samples?

Chi-square test

Independent samples t-test

Paired t-test

ANOVA

13. True or False: A 95% confidence interval and a two-tailed test at α = 0.05 are directly related.

True

False

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15. Which of the following is the correct decision rule for hypothesis testing at α = 0.05?

Reject H₀ if p-value < 0.05

Reject H₀ if p-value > 0.05

Reject H₀ if p-value = 0.05

Reject H₀ if the sample mean is large

16. True or False: A small p-value (e.g., 0.02) provides strong evidence against the null hypothesis.

True

False

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18. If the significance level (α) is set to 0.05, what does this mean?

There is a 5% chance the alternative hypothesis is true

We accept a 5% risk of rejecting a true null hypothesis

95% of the sample data is correct

The p-value must equal exactly 0.05

Submit

20. What does a p-value represent in hypothesis testing?

The probability that the null hypothesis is true

The probability of observing the data if the null hypothesis is true

The effect size of the test

The power of the statistical test

Data+ Hypothesis Testing Fundamentals Quiz

1. What is the alternative hypothesis (H₁) in a two-tailed test for comparing two means?

2.

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

2. True or False: Rejecting the null hypothesis proves that the alternative hypothesis is true.

3. ANOVA is used to compare means across ____ or more groups.

4. Which condition violates the assumption of independence in a paired t-test?

5. True or False: The significance level α is the same as the p-value.

6. The ____ hypothesis is what we assume to be true before collecting data.

7. A p-value of 0.001 is compared to α = 0.05. What is the correct decision?

8. When comparing categorical variables across groups, which test is appropriate?

9. True or False: A hypothesis test with a larger sample size generally has greater statistical power.

10. The test statistic in a t-test measures the ____ between the sample mean and the hypothesized population mean, relative to the standard error.

11. In hypothesis testing, the null hypothesis (H₀) represents what assumption?

12. Which test would you use to compare the means of two independent samples?

13. True or False: A 95% confidence interval and a two-tailed test at α = 0.05 are directly related.

14. The ____ is the probability of correctly rejecting the null hypothesis when it is false.

15. Which of the following is the correct decision rule for hypothesis testing at α = 0.05?

16. True or False: A small p-value (e.g., 0.02) provides strong evidence against the null hypothesis.

17. A Type II error occurs when we fail to reject the null hypothesis when it is actually false. This error is also called a ____ error.

18. If the significance level (α) is set to 0.05, what does this mean?

19. A Type I error occurs when we ____.

20. What does a p-value represent in hypothesis testing?