Practice Quiz

Chapter 13
Understanding Research Results: Statistical Inference

Here are some questions for a practice quiz. The questions are multiple-choice and true-false. They may not resemble the questions that your instructor may ask on a test. That is, the questions on your class exams may be more difficult and may include essay and short answer questions.

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1. Statistical significance tests allow you to make inferences about population values based on data obtained from samples.
True
False

2. After conducting a statistical test, you conclude that the mean score of males differs significantly from the mean score of females. You have:
accepted the null hypothesis
rejected the null hypothesis
made a Type I error

3. With larger sample sizes, your sample data are more likely to accurately reflect true population values.
True
False

4. You did not reject the null hypothesis. It is possible that you made a:
Type I error.
Type II error.
Type I and a Type II error.

5. To increase the likelihood of obtaining a significant result, you should have a:
large difference between groups.
small variabilility within groups.
both of these are true.

6. In addition to knowing about the statistical significance of your data, it is important to know about effect size, the strength of the relationship between your variables.
True
False

7. When you conduct a t-test, your obtained data are transformed into a single obtained t value. A ____________ of t values exists to allow you to know the probability that your data are consistent with the null hypothesis.
sampling distribution
random probability distribution
Type I error table

8. The probability of correctly rejecting the null hypothesis is called:
alpha
beta
power

9. Another term for systematic variance is between-group variance. Another term for error variance is within-group variance. 
True
False

10. When designing a study, it is possible to calculate the sample size that will be needed to obtain a statistically significant effect. This calculation is called:
Type II error analysis.
effect size analysis.
power analysis.

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