Chapter 8: Generalizing from Research Results: Inferential Statistics

Test Bank

Multiple Choice

1. For a t test comparing two groups that consist of the same individuals, we use the t test for ______ samples.

a. independent

b. dependent

c. asymmetric

d. symmetric

Learning Objective: 8.4: Describe and compute a t test.

Cognitive Domain: Knowledge

Answer Location: The t Test

Difficulty Level: Easy

2. For a t test comparing two groups that consist of different individuals, we use the t test for ______ samples.

a. independent

b. dependent

c. asymmetric

d. symmetric

Learning Objective: 8.4: Describe and compute a t test.

Cognitive Domain: Knowledge

Answer Location: The t Test

Difficulty Level: Easy

3. Conceptually, the t test is based on ______.

a. the mode scores on the same variable for two different groups

b. the differences in means for a variable common to two groups

c. the population

d. size of correlation between groups

Learning Objective: 8.4: Describe and compute a t test.

Cognitive Domain: Application

Answer Location: The t Test

Difficulty Level: Hard

4. What does the t test compare?

a. the mean scores of two groups on the same variable to determine the probability that the groups are different

b. the mean scores of two variables to see if they belong to the same group

c. the skew of two different samples to see if they come from the same population

d. the skew of two different samples to see which distribution is closest to the normal distribution

Learning Objective: 8.4: Describe and compute a t test.

Cognitive Domain: Comprehension

Answer Location: The t Test

Difficulty Level: Medium

5. The formula for standard deviation for a set of scores includes ______.

a. the population from which the sample is chosen

b. the median for the set of scores

c. each individual score

d. the mode for the set of scores

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: The Normal Curve, z Scores, and the Return of Standard Deviation

Difficulty Level: Medium

6. Nonparametric statistics should be used when we ______.

a. cannot assume we have normally distributed data

b. can assume we have normally distributed data

c. do not know the sample size

d. have continuous variables

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Application

Answer Location: z scores, Hypotheses, and Decision Making

Difficulty Level: Hard

7. Inferential statistics tell us that as long as we are prepared to accept a known level of uncertainty in our projections, ______.

a. we do not need huge sample sizes

b. we do need huge sample sizes

c. sample size is irrelevant

d. we can use any sampling method

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Comprehension

Answer Location: z scores, Hypotheses, and Decision Making

Difficulty Level: Medium

8. A range of values calculated from a sample is called the ______.

a. confidence metric

b. confidence interval

c. error interval

d. confidence level

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: z scores, Hypotheses, and Decision Making

Difficulty Level: Medium

9. For a sampling distribution (the distribution of the sample results), the standard deviation is referred to as the ______.

a. standard distribution

b. standard sample

c. standard error

d. standard curve

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: z Scores, Hypotheses, and Decision Making

Difficulty Level: Medium

10. The probability of sampling any value under the normal curve is ______.

a. 0

b. 0.25

c. 0.50

d. 1.00

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Knowledge

Answer Location: The Normal Curve, z Scores, and the Return of Standard Deviation

Difficulty Level: Easy

11. The probability of sampling any value under the normal curve that is greater than the mean is ______.

a. 0

b. 0.25

c. 0.50

d. 1.0

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Knowledge

Answer Location: The Normal Curve, z Scores, and the Return of Standard Deviation

Difficulty Level: Easy

12. The probability of sampling any value under the normal curve that is less than the mean is ______.

a. 0

b. 0.25

c. 0.50

d. 1.0

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Knowledge

Answer Location: The Normal Curve, z Scores and the Return of Standard Deviation

Difficulty Level: Easy

13. The z distribution allows us to calculate ______.

a. the strength of the relationship between two variables

b. the strength of the relationships among three or more variables

c. the value of one variable given a value for a related variable

d. the probability that a sample has captured the characteristics of the population from which it was drawn

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Application

Answer Location: The Normal Curve, z Scores, and the Return of Standard Deviation

Difficulty Level: Medium

14. In a normal distribution, most values are ______.

a. in the middle of the distribution

b. evenly distributed

c. to the right of the mean value

d. to the left of the mean value

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: The Normal Curve and the Central Limit Theorem

Difficulty Level: Medium

15. A curve that is steep or high relative to the normal curve is described as ______.

a. neokurtic

b. platykurtic

c. leptokurtic

d. multikurtic

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: The Language of Curves

Difficulty Level: Medium

16. A curve that is flat relative to the normal curve is described as ______.

a. neokurtic

b. platykurtic

c. leptokurtic

d. monokurtic

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: The Language of Curves

Difficulty Level: Medium

17. When data are skewed, which of the following statistics are NOT necessary to adequately describe the data?

a. mean

b. median

c. mode

d. chi-square

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Application

Answer Location: The Language of Curves

Difficulty Level: Hard

18. A data plot showing a positive skew has ______.

a. the “tail” of the plot in the low numbers

b. the “tail” of the plot in the high numbers

c. a flat profile

d. a high profile

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: The Language of Curves

Difficulty Level: Medium

19. A data plot showing a negative skew has ______.

a. the “tail” of the plot in the low numbers

b. the “tail” of the plot in the high numbers

c. a flat profile

d. a high profile

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: The Language of Curves

Difficulty Level: Medium

20. A tri-modal profile means that a distribution of data plots out showing _______ peak(s).

a. zero

b. one

c. two

d. three

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: The Language of Curves

Difficulty Level: Medium

21. A bi-modal profile means that a distribution of data plots out showing ______ peak(s).

a. zero

b. one

c. two

d. three

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: The Language of Curves

Difficulty Level: Medium

22. Inferential statistics are based on the assumption(s) EXCEPT ______.

a. a normal distribution of values in a population

b. random sampling of the population

c. every individual in a sample having an equal chance of being sampled

d. snowball sampling

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Application

Answer Location: Generalizing From Data: Inferential Statistics

Difficulty Level: Medium

23. The extent to which sample data reflect the wider population from which the sample was drawn can be estimated using which one of the following?

a. unilateral statistics

b. descriptive statistics

c. inferential statistics

d. essential statistics

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Comprehension

Answer Location: Generalizing From Data: Inferential Statistics

Difficulty Level: Medium

24. What do correlation coefficients indicate?

a. strength of the relationship between two variables

b. direction of the relationship between two variables

c. strength of the relationships among three or more variables

d. direction of the relationship among three or more variables

Learning Objective: 8.6: Compare and contrast the concepts of correlation and regression.

Cognitive Domain: Comprehension

Answer Location: Correlation

Difficulty Level: Medium

25. What does MANOVA stand for?

a. multiple analysis of variables

b. multivariate analysis of vectors

c. multivariate analysis of variance

d. multiple analysis of variance

Learning Objective: 8.5: Explain the concept of analysis of variance.

Cognitive Domain: Comprehension

Answer Location: ANOVA: Example

Difficulty Level: Medium

26. Linear regression assumes a relationship between variables that is best captured by ______.

a. a histogram

b. cross-tabulations

c. a curved line

d. a straight line

Learning Objective: 8.6: Compare and contrast the concepts of correlation and regression.

Cognitive Domain: Application

Answer Location: Regression

Difficulty Level: Medium

27. What does one-way ANOVA compare?

a. one variable across one group

b. one variable across two or more groups

c. two or more variables across one group

d. two or more variables across two or more groups

Learning Objective: 8.5: Explain the concept of analysis of variance.

Cognitive Domain: Comprehension

Answer Location: Analysis of Variance

Difficulty Level: Medium

28. The two tests most commonly used to see if two groups differ in some way are ______.

a. t test and correlation

b. correlation and standard deviation

c. correlation and chi-square test

d. t test and chi-square test

Learning Objective: 8.4: Describe and compute a t test.

Cognitive Domain: Comprehension

Answer Location: Testing for Differences Between and Among Groups

Difficulty Level: Medium

29. What does the t test compare?

a. mean scores on one variable in two different groups

b. distribution of scores in two different groups

c. mean number of individuals in two different groups

d. mean number of variables in two different groups

Learning Objective: 8.4: Describe and compute a t test.

Cognitive Domain: Comprehension

Answer Location: The t Test

Difficulty Level: Medium

30. ANOVA is a ______ statistic.

a. multivariate

b. univariate

c. bivariate

d. unvariate

Learning Objective: 8.5: Explain the concept of analysis of variance.

Cognitive Domain: Comprehension

Answer Location: Analysis of Variance

Difficulty Level: Medium

31. Interpreting a t value requires that we also compute a number known as the degrees of ______.

a. randomness

b. meanness

c. freedom

d. variance

Learning Objective: 8.4: Describe and compute a t test.

Cognitive Domain: Application

Answer Location: The t Test

Difficulty Level: Medium

32. The t test is used to assess whether groups differ on which of the following types of variable?

a. nominal and ordinal

b. interval and ratio

c. linear and curvilinear

d. bivariate and univariate

Learning Objective: 8.4: Describe and compute a t test.

Cognitive Domain: Comprehension

Answer Location: The t Test

Difficulty Level: Medium

33. The properties of a normal curve are such that ______ of the values under it occur plus or minus 1 standard deviation from the mean.

a. 33%

b. 50%

c. 68%

d. 95%

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: The Normal Curve, z Scores and the Return of Standard Deviation

Difficulty Level: Hard

34. The properties of a normal curve are such that ______ of the values under it occur plus or minus 2 standard deviations from the mean.

a. 50%

b. 68%

c. 95%

d. 99%

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Comprehension

Answer Location: The Normal Curve, z Scores and the Return of Standard Deviation

Difficulty Level: Hard

35. Type I error is deciding that ______.

a. a relationship is linear when it is not

b. you have no significant result when in fact you do

c. you have a significant finding when in fact you do not

d. sample size is inadequate when it is adequate

Learning Objective: 8.7: Define Type I and Type II errors.

Cognitive Domain: Application

Answer Location: Accept Or Reject My Findings?

Difficulty Level: Medium

36. Type II error is deciding that ______.

a. a relationship is linear when it is not

b. you have no significant result when in fact you do

c. you have a significant finding when in fact you do not

d. sample size is inadequate when it is adequate

Learning Objective: 8.7: Define Type I and Type II errors.

Cognitive Domain: Application

Answer Location: Accept Or Reject My Findings?

Difficulty Level: Medium

True/False

1. “To what extent do my sample data reflect the wider population from which I sampled?” is a question that inferential statistics cannot answer.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Application

Answer Location: Generalizing from Data: Inferential Statistics

Difficulty Level: Medium

2. Inferential statistics are based on the assumption that the sampled population has normally distributed characteristics.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Comprehension

Answer Location: Generalizing from Data: Inferential Statistics

Difficulty Level: Medium

3. Inferential statistics are based on the assumption that the sample studied is randomly selected.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Knowledge

Answer Location: Generalizing from Data: Inferential Statistics

Difficulty Level: Easy

4. Inferential statistics allow us to make an inference about a wider population with 100% certainty.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Comprehension

Answer Location: Generalizing from Data: Inferential Statistics

Difficulty Level: Medium

5. With inferential statistics, we do not need large sample sizes as long as we are prepared to accept a known level of uncertainty in our projections from a sample.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Knowledge

Answer Location: z Scores, Hypotheses and Decision Making

Difficulty Level: Easy

6. Inferential statistics let us calculate a level of certainty when we project results from a sample to a wider population.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Knowledge

Answer Location: z Scores, Hypotheses and Decision Making

Difficulty Level: Easy

7. For a sampling distribution (the distribution of sample results), the standard deviation is called the standard error.

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Knowledge

Answer Location: z Scores, Hypotheses and Decision Making

Difficulty Level: Easy

8. This range of possible values calculated for a particular level of confidence is called the confidence interval.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Knowledge

Answer Location: z Scores, Hypotheses and Decision Making

Difficulty Level: Easy

9. Correlation is a measure of the strength of the relationship between two variables.

Learning Objective: 8.6: Compare and contrast the concepts of correlation and regression.

Cognitive Domain: Knowledge

Answer Location: Correlation

Difficulty Level: Easy

10. Correlation shows the shape of the relationship between two variables.

Learning Objective: 8.6: Compare and contrast the concepts of correlation and regression.

Cognitive Domain: Knowledge

Answer Location: Correlation

Difficulty Level: Easy

11. A curvilinear relationship and a straight-line relationship between the two variables can exist simultaneously.

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Knowledge

Answer Location: The Language of Curves

Difficulty Level: Easy

12. A significant correlation between two variables means that there is a causal relationship between them.

Learning Objective: 8.6: Compare and contrast the concepts of correlation and regression.

Cognitive Domain: Comprehension

Answer Location: Correlation

Difficulty Level: Medium

13. In a statistically perfect world, data conform to a symmetrical so-called normal curve.

Learning Objective: 8.2: Describe the normal curve and its significance to inferential statistics.

Cognitive Domain: Knowledge

Answer Location: The Language of Curves

Difficulty Level: Easy

14. Both the t test and the chi-square test look for differences in average scores between two groups.

Learning Objective: 8.4: Describe and compute a t test.

Cognitive Domain: Comprehension

Answer Location: Testing for Differences Between and Among Groups

Difficulty Level: Medium

15. The t test assesses the differences in mean scores between two groups.

Learning Objective: 8.4: Describe and compute a t test.

Cognitive Domain: Knowledge

Answer Location: The t Test

Difficulty Level: Easy

Essay

1. Explain the purpose of the t test and the chi-square test and the difference between them.

Learning Objective: 8.4: Describe and compute a t test.

Cognitive Domain: Application

Answer Location: Testing for Differences Between and Among Groups

Difficulty Level: Hard

2. Explain the difference between inferential and descriptive statistics.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Comprehension

Answer Location: Generalizing from Data: Inferential Statistics

Difficulty Level: Medium

3. A newspaper reports from a survey that college students study on average 7 hours a week for their classes. Identify the statistics and any other information you would want to know from this survey before making generalizations about the student population at large, and explain why.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Analysis

Answer Location: Generalizing from Data: Inferential Statistics

Difficulty Level: Hard

4. You are designing a survey with the objective of comparing how male and female students differ in their use of social media. Outline the measures you would use and explain the statistics you would report for each measure in your final report.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Analysis

Answer Location: Generalizing from Data: Inferential Statistics

Difficulty Level: Hard

5. Explain the concept of statistical significance.

Learning Objective: 8.3: Explain the concept of statistical significance and its relevance to interpreting research findings.

Cognitive Domain: Application

Answer Location: Chapter Overview

Difficulty Level: Hard

6. Explain how inferential statistics differ from descriptive statistics in the insights they can provide researchers.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Application

Answer Location: Generalizing from Data: Inferential Statistics

Difficulty Level: Hard

7. Identify two assumptions on which inferential statistics are based.

Learning Objective: 8.1: Explain the concept of inferential statistics and how they differ from descriptive statistics.

Cognitive Domain: Comprehension

Answer Location: Generalizing from Data: Inferential Statistics

Difficulty Level: Medium

8. Define Type I error.

Learning Objective: 8.7: Define Type I and Type II errors.

Cognitive Domain: Comprehension

Answer Location: Accept or Reject My Findings?

Difficulty Level: Medium

9. Define Type II error.

Learning Objective: 8.7: Define Type I and Type II errors.

Cognitive Domain: Comprehension

Answer Location: Accept or Reject My Findings?

Difficulty Level: Medium