Error, Alpha, Beta, and Power

Other things being equal, which of the following actions will reduce the power of a hypothesis test?

I. Increasing sample size

II. Increasing Significance Level

III. Increasing beta, the probability of a Type II error

• I only

• II only

• III only

• All of the above

• None of the above

Suppose a researcher conducts an experiment to test a hypothesis. If she doubles her sample size, which of the following will increase?

I. The power of the hypothesis test.

II. the probability of making a Type I error.

III. The probability of making a Type II error

• I only

• II only

• III only

• All of the above.

• None of the above.

As alpha increases, how is the power of the study affected?

• It is not affected.

• It is decreased.

• It approaches 0

• It is increased

• None of the above

As the sample size increases, how is the power of the study affected?

• It is increased.

• It is decreased.

• It approaches 0.

• It is not affected.

• None of the above

If the probability of making a type II error is 0.3, what is the power of the analysis?

• 30

• 1.3

• .09

• .7

• None of the above

Which of the following alphas would be associated with the greatest statistical power?

• .05

• .1

• 0.025

• .01

Which of the following alphas would be associated with the greatest likelihood of making a type II error?

• 0.005

• 0.0001

• 0.001

• 0.01

When a researcher decreases the risk of making a type I error, the risk of making a type II error is?

• Decreased.

• Not affected.

• Equal to the chance of making a type I error.

• Increased.

• None of the above

A Type II error is committed when

• we reject a null hypothesis that is true.

• we don't reject a null hypothesis that is true.

• we reject a null hypothesis that is false.

• we don't reject a null hypothesis that is false.

A Type I error is committed when

• we reject a null hypothesis that is true.

• we don't reject a null hypothesis that is true.

• we reject a null hypothesis that is false.

• we don't reject a null hypothesis that is false.