Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
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
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
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
4. What does the t test compare?
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
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
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
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
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
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
8. A range of values calculated from a sample is called the ______.
a. confidence metric
b. confidence interval
c. error interval
d. confidence level
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
10. The probability of sampling any value under the normal curve is ______.
a. 0
b. 0.25
c. 0.50
d. 1.00
11. The probability of sampling any value under the normal curve that is greater
than the mean is ______.
a. 0
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
b. 0.25
c. 0.50
d. 1.0
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
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
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
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
15. A curve that is steep or high relative to the normal curve is described as
______.
a. neokurtic
b. platykurtic
c. leptokurtic
d. multikurtic
16. A curve that is flat relative to the normal curve is described as ______.
a. neokurtic
b. platykurtic
c. leptokurtic
d. monokurtic
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
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
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
c. a flat profile
d. a high profile
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
20. A tri-modal profile means that a distribution of data plots out showing
_______ peak(s).
a. zero
b. one
c. two
d. three
21. A bi-modal profile means that a distribution of data plots out showing ______
peak(s).
a. zero
b. one
c. two
d. three
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
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
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
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
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
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
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
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
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
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
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
30. ANOVA is a ______ statistic.
a. multivariate
b. univariate
c. bivariate
d. unvariate
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
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
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%
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
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%
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
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
True/False
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
1. “To what extent do my sample data reflect the wider population from which I
sampled?” is a question that inferential statistics cannot answer.
2. Inferential statistics are based on the assumption that the sampled population
has normally distributed characteristics.
3. Inferential statistics are based on the assumption that the sample studied is
randomly selected.
4. Inferential statistics allow us to make an inference about a wider population
with 100% certainty.
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.
6. Inferential statistics let us calculate a level of certainty when we project results
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
from a sample to a wider population.
7. For a sampling distribution (the distribution of sample results), the standard
deviation is called the standard error.
8. This range of possible values calculated for a particular level of confidence is
called the confidence interval.
9. Correlation is a measure of the strength of the relationship between two
variables.
10. Correlation shows the shape of the relationship between two variables.
11. A curvilinear relationship and a straight-line relationship between the two
variables can exist simultaneously.
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
12. A significant correlation between two variables means that there is a causal
relationship between them.
13. In a statistically perfect world, data conform to a symmetrical so-called
normal curve.
14. Both the t test and the chi-square test look for differences in average scores
between two groups.
15. The t test assesses the differences in mean scores between two groups.
Essay
1. Explain the purpose of the t test and the chi-square test and the difference
between them.
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
2. Explain the difference between inferential and descriptive statistics.
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.
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.
5. Explain the concept of statistical significance.
Instructor Resource
Treadwell and Davis, Introducing Communication Research: Paths of Inquiry, 4e
SAGE Publishing, 2020
6. Explain how inferential statistics differ from descriptive statistics in the insights
they can provide researchers.
7. Identify two assumptions on which inferential statistics are based.
8. Define Type I error.
9. Define Type II error.