AP Statistics Flashcards: Potential Errors When Performing Tests
Written by AP Content Team, Verified for 2026 AP Exams, Last updated: May 2026
Review key ideas with interactive flashcards. This set includes 21 cards to help you master important concepts.
What is a Type II error?
A Type II error occurs when a false null hypothesis is not rejected. This is also known as a false negative.
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What is a Type II error?
A Type II error occurs when a false null hypothesis is not rejected. This is also known as a false negative.
Define the significance level, alpha (α).
The significance level, alpha, is the probability of making a Type I error, assuming the null hypothesis is true.
Under what condition is it possible to make a Type I error?
A Type I error can only be made when the null hypothesis is true but is rejected by the test.
What determines how we interpret the consequences of Type I and Type II errors?
The consequences of Type I and Type II errors depend on the specific situation and context of the test.
What is the goal of a significance test in relation to a false null hypothesis?
The goal is to correctly reject a false null hypothesis, the probability of which is the power of the test.
What factor primarily influences the choice of a significance level (alpha)?
The choice of significance level is influenced by the consequences of a Type I error.
A study fails to reject the null hypothesis that a pesticide is safe. Later, the pesticide is found to cause harm. What error occurred?
A Type II error occurred because a false null hypothesis (the pesticide is safe) was not rejected.
How is the probability of a Type II error calculated using the power of a test?
The probability of a Type II error is calculated as 1 minus the power of the test.
What is the relationship between the significance level (α) and the probability of a Type I error?
The significance level, alpha, is the probability of making a Type I error if the null hypothesis is true.
If a significance test has a power of 0.80, what is the probability of a Type II error?
The probability of a Type II error is 1 - 0.80 = 0.20.
How does the effect size influence the probability of a Type II error?
The probability of a Type II error decreases as the effect size increases.
Identify three factors that, when increased, decrease the probability of a Type II error.
The probability of a Type II error decreases as sample size, significance level, or effect size increases.
A researcher is concerned about the serious consequences of a false positive. How should they adjust their significance level, alpha?
They should choose a lower significance level, as alpha is the probability of a Type I error (false positive).
A new drug is approved after a study rejects the null hypothesis that it has no effect. Later, it's found to be ineffective. What error occurred?
A Type I error occurred because a true null hypothesis (the drug has no effect) was rejected.
How does a decrease in standard error affect the probability of a Type II error?
The probability of a Type II error decreases as the standard error decreases.
What is the power of a test?
The power of a test is the probability of correctly rejecting a false null hypothesis.
What is a 'false positive' in the context of hypothesis testing?
A false positive is a Type I error, which occurs when a true null hypothesis is rejected.
What is a 'false negative' in the context of hypothesis testing?
A false negative is a Type II error, which occurs when a false null hypothesis is not rejected.
How does increasing the sample size affect the probability of a Type II error?
The probability of a Type II error decreases as the sample size increases.
What is a Type I error?
A Type I error occurs when a true null hypothesis is rejected. This is also known as a false positive.
What is the effect of increasing the significance level (α) on the probability of a Type II error?
The probability of a Type II error decreases as the significance level increases.