All Flashcards
What are the differences between Type I and Type II errors?
Type I: Reject true null (false positive), probability α. | Type II: Fail to reject false null (false negative), probability β.
What are the differences between Power and β?
Power: Probability of correctly rejecting a false null. | β: Probability of failing to reject a false null.
Explain the concept of Type I error.
Concluding there is an effect when there isn't. Probability is α.
Explain the concept of Type II error.
Failing to detect a real effect. Probability is β.
Explain the concept of Power.
The probability of correctly rejecting a false null hypothesis; detecting a real effect.
Explain how increasing sample size affects power.
Larger samples provide more information and reduce variability, making it easier to detect a true effect, thus increasing power.
Explain how increasing significance level (α) affects the probability of Type II error (β).
Increasing α increases the chance of rejecting H₀, even if it's false, thus decreasing β.
What is a Type I error?
Rejecting a true null hypothesis (false positive).
What is a Type II error?
Failing to reject a false null hypothesis (false negative).
What is power of a test?
The probability of correctly rejecting a false null hypothesis.
What is significance level (α)?
The probability of making a Type I error.
What is β (beta)?
The probability of making a Type II error.