Hypothesis Testing Flashcards

A result with p = 0.001 compared to p = 0.04 (both significant at α = 0.05) means:

Answer: The first result provides stronger evidence against H₀

A smaller p-value indicates the observed data are even more inconsistent with H₀, providing stronger statistical evidence against it.

Which statement correctly distinguishes statistical significance from practical significance?

Answer: A result can be statistically significant yet have a trivially small effect size

With very large samples, even tiny, unimportant differences can become statistically significant; effect size measures practical significance.

In hypothesis testing, what does 'fail to reject H₀' mean?

Answer: There is insufficient evidence to conclude H₀ is false

Failing to reject H₀ means the data do not provide enough evidence against it — it does not prove H₀ is true.

A left-tailed test rejects H₀ when the test statistic is:

Answer: Less than the negative critical value

In a left-tailed test, extreme negative values of the test statistic provide evidence against H₀, so rejection occurs below the negative critical value.

Which of the following would reduce the risk of both Type I and Type II errors simultaneously?

Answer: Increasing the sample size

Increasing sample size reduces sampling variability, which decreases the probability of both error types simultaneously.

The F-statistic in ANOVA is calculated as:

Answer: Variance between groups / Variance within groups

The F-statistic is the ratio of between-group variance to within-group variance; a large F suggests the group means differ more than chance explains.

A hypothesis test on proportions uses which test statistic distribution?

Answer: Standard normal (z) distribution

Tests for a single proportion or difference between two proportions rely on the standard normal (z) distribution when sample sizes are sufficiently large.