Hypothesis Testing Flashcards

Which factor does NOT directly increase the power of a hypothesis test?

Answer: Raising the significance level α

Raising α increases power but at the cost of a higher Type I error rate; reducing SD or increasing n/effect size raises power without that trade-off.

A z-test is appropriate when:

Answer: The population variance is known or n is large

A z-test is used when the population standard deviation is known or the sample size is large enough for the Central Limit Theorem to apply.

What is a p-value?

Answer: The probability of observing a result at least as extreme as the sample result, assuming H₀ is true

The p-value measures how likely the observed data (or more extreme) would be if the null hypothesis were true.

In a paired t-test, what is being compared?

Answer: Differences within the same subjects measured twice

A paired t-test analyzes the mean difference between two measurements taken on the same subject or matched pairs.

A confidence interval for a mean does not include zero. What does this imply about the two-tailed hypothesis test at the matching α level?

Answer: Reject H₀: μ = 0

If zero falls outside the confidence interval, it means the null value is implausible, which corresponds to rejecting H₀ at the matching significance level.

Which statement about the null hypothesis (H₀) is correct?

Answer: It always states there is no effect or no difference

H₀ is the default assumption of no effect, no difference, or no relationship that the test attempts to refute.

A researcher increases sample size from 50 to 200. Holding everything else constant, what happens to the standard error?

Answer: It is halved

Standard error = σ/√n; quadrupling n (50→200) means √n doubles, so SE is halved.