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10 Multiple Choice Questions in Hypothesis testing

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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 ì = 80. The results will be examined using a one-tailed hypothesis test. Which of the following is the correct statement of the null hypothesis?
ì < 80
ì > 80
ì >= 80
ì <=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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Answers to 10 Multiple Choice Questions in Hypothesis testing have been provided.

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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. ...

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