9.1.4 - Relationships between Errors and Power

The probability of a type I error is

• alpha

• beta

• sigma

• mu

The probability of a type II error is

• alpha

• beta

• sigma

• mu

Which of the following correctly describes a type II error?

• Rejecting a false Ho

• Failing to reject a false Ho

• Rejecting a true Ho

• Failing to reject a true Ho

What is the Power of a test?

• A strong force
• The probability that we correctly reject a false null.
• The probability that we correctly accept a true null.
• How tough it is.

The alpha level is

• Always the same as the p value

• The pre-set threshold for significance

• The sample size

• The power

An increase in sample size will decrease

• the chance of type I error
• the chance of type II error
• the power
• the love

a lower alpha level will increase a test's

• chance of type I error
• chance of type II error
• power
• blood pressure

Which of the following statements is FALSE?

• The power of the test increases as α increases.
• The power of a test does not depend on the sample size.
• The power of a test is the complement of a Type II error.
• As the α-level increases, P(Type II error) decreases.

A researcher plans to conduct a test of hypotheses at the α = 0.01 significance level.  She designs her study to have a power of 0.90 at a particular alternative value of the parameter of interest.  The probability that the researcher will commit a Type I error is

• 0.01
• 0.10
• 0.90
• 0.99

Which of the following will increase the power of a statistical test of significance

• Increase the Type II error probability
• Increase the sample size
• Decrease the α level
• All of the above