Exam Questions Chapter 15 Inferential Data Analysis

Chapter 15

Inferential Data Analysis

Multiple Choice

1. When a researcher says after a statistical test, “the difference is significant,” he or she is saying that:

A. the sample statistic value and the hypothesized value are not the same.
B. the difference between the sample statistic value and the hypothesized value is statistically different.
C. the research hypothesis and statistical hypothesis are not in agreement.
D. the main or null hypothesis seems to be true.
E. the findings of the research study have significant implications.

2. A researcher conducted an experiment in which he compared two methods of teaching. If there were 10 people in Group 1 and 12 in Group 2, and a two-tailed t-test for two independent groups at alpha 0.05 was conducted, what t-value was needed to reject H0?

A. 2.093
B. 2.086
C. 2.080
D. 2.074
E. None of these is correct.

3. A researcher reported that there were two independent groups with 25 in each group. Each group received a different treatment. An alpha value of 0.05 was used. Based on the data analysis using a computer, t = 2.11, p = 0.03, group 1 mean = 88, and group 2 mean = 81. Based on this information, identify the true answer.

A. The null hypothesis is accepted.
B. The alternate hypothesis that the population 1 mean is larger is accepted.
C. The alternate hypothesis that the population 2 mean is larger is accepted.
D. Based on the information provided, it is impossible to make a decision.
E. Based on the information provided, the researcher could have made two different decisions.

4. Select the false statement below.

A. If a null hypothesis is false, but the researcher is able to reject it, a type II error has occurred.
B. If a researcher selects an alpha level of 0.01, there is a 1% chance of a type I error.
C. A type I error is guarded against more than a type II error by most researchers.
D. If a null hypothesis is true, but the researcher is able to reject it, this is a type I error.
E. If a researcher uses an alpha level of 0.10 rather than 0.05, there is less chance of a type II error.

5. Identify the false statement about two-group comparisons after ANOVA.

A. They are recommended after a significant F test when there are three or more groups.
B. The two-independent-group t-test is a common two-group comparison method.
C. Their purpose is to identify which means significantly differ from each other.
D. Two common two-group comparison techniques are Scheffe and Tukey.
E. They are not used when the F is nonsignificant.

6. Select the false statement below concerning chi-square tests.

A. The hypothesis tested in a two-way chi-square is that two measures are independent of each other.
B. If a two-way chi-square was conducted with a year in college (4 levels) vs. attitude (5 levels), the degrees of freedom (d.f.) value = 12.
C. The hypothesis tested in a one-way chi-square is normal distribution.
D. The chi-square test may be conducted with nominal data like gender.
E. Chi-square tests are commonly used with data from a questionnaire.

7. When a ANOVA is found statistically significant, follow-up tests should be conducted to determine which pair of the means is different from each other. The follow-up test is also known as the:

A. post-test.

B. post-hoc test.

C. planned comparison.

D. significant test.

8. The key difference of inferential statistics from descriptive statistics is that it:

A. uses sample information to guess the population’s parameter.
B. studies the whole population so that the population parameter can be learned.
C. uses sample information to guess another population’s parameter.
D. simply computes the population’s parameter directly.

9. Type I error occurs when:

A. a false null hypothesis is rejected.
B. a false null hypothesis is not rejected.
C. a true null hypothesis is rejected.
D. a true null hypothesis is not rejected.

10. Type II error occurs when:

A. a false null hypothesis is rejected.
B. a false null hypothesis is not rejected.
C. a true null hypothesis is rejected.
D. a true null hypothesis is not rejected.