# 10 Multiple Choice Questions in Hypothesis testing

1. Whenever your decision is to reject the null hypothesis, there is a risk of a Type I error.

True

False

2. A Type I error occurs when you conclude that a treatment effect exists, but the treatment has no effect.

True

False

3. The critical region consists of extreme sample values that are very unlikely to occur if the null hypothesis is true.

True

False

4. Changing a (alpha) from .05 to .01 increases the risk of a Type I error.

True

False

5. Researchers compute measures of effect size because finding a significant treatment effect in a hypothesis test does not necessarily mean that there is a large treatment effect.

True

False

6. Which alpha level provides the smallest chance of committing a Type I error?

a (alpha) = .025

a (alpha) = .10

a (alpha) = .01

a (alpha) = .05

7. A Type I error is defined as

rejecting a true null hypothesis

failing to reject a false null hypothesis

rejecting a false null hypothesis

failing to reject a true null hypothesis

8. A researcher is conducting an experiment to evaluate a treatment that is expected to increase the scores for individuals in a population which is known to have a mean of Ã¬ = 80. The results will be examined using a one-tailed hypothesis test. Which of the following is the correct statement of the null hypothesis?

Ã¬ < 80

Ã¬ > 80

Ã¬ >= 80

Ã¬ <=80

9. A researcher is conducting a one-tailed test with a (alpha) = .01 to determine whether a treatment produces a significant increase in scores. What z-score value(s) would define the critical region for this test?

beyond -2.58

beyond +2.33

beyond +2.58

beyond -2.33

10. A sample of n = 25 individuals is selected from a population with mean = 60 and standard deviation = 10 and a treatment is administered to the sample. After treatment, the sample mean is M = 63. What is the value of Cohen's d for this sample?

0.30

cannot answer without additional information

1.50

10.0

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#### Solution Preview

1. Whenever your decision is to reject the null hypothesis, there is a risk of a Type I error.

True

False

Answer: True

Rejecting Null Hypothesis when true is type I error. Accepting Null Hypothesis when false is Type II error.

2. A Type I error occurs when you conclude that a treatment effect exists, but the treatment has no effect.

True

False

Answer: True

Treatment effect exists is the Alternative hypothesis. In a type I error we reject the Null hypothesis - accept that a treatment effect exists where none exists.

3. The critical region consists of extreme sample values that are very unlikely to occur if the null hypothesis is true.

True

False

Answer: True

4. ...

#### Solution Summary

Answers to 10 Multiple Choice Questions in Hypothesis testing have been provided.