This document contains discussion questions and exercises related to analyzing research data. It includes questions about defining key terms, handling missing data, developing coding categories, interpreting results of cross-tabulations and hypothesis tests, and choosing appropriate statistical analyses. Sample data and studies are presented throughout for participants to practice working with. The final section profiles an individual's results on a life styles inventory, including their scores on 12 thinking and behavior styles.

1. Discussion Questions Chapter 15
Terms in Review
1
Define or explain:
1. Coding rules.
2. Spreadsheet data entry.
3. Bar codes.
4. Precoded instruments.
5. Content analysis.
6. Missing data.
7. Optical mark recognition.
2
How should the researcher handle “don’t know” responses?
Making Research Decisions
3
A problem facing shoe store managers is that many shoes
eventually must be sold at markdown prices. This prompts us to
conduct a mail survey of shoe store managers in which we ask,
What methods have you found most successful for reducing the
problem of high markdowns? We are interested in extracting as
much information as possible from these answers to better
understand the full range of strategies that store managers use.
Establish what you think are category sets to code 500
responses similar to the 14 given here. Try to develop an
integrated set of categories that reflects your theory of
markdown management. After developing the set, use it to code
the 14 responses.

2. 1. Have not found the answer. As long as we buy style shoes,
we will have markdowns. We use PMs on slow merchandise, but
it does not eliminate markdowns. (PM stands for “push-
money”—special item bonuses for selling a particular style of
shoe.)
2. Using PMs before too old. Also reducing price during season.
Holding meetings with salespeople indicating which shoes to
push.
3. By putting PMs on any slow-selling items and promoting
same. More careful check of shoes purchased.
4. Keep a close watch on your stock, and mark down when you
have to—that is, rather than wait, take a small markdown on a
shoe that is not moving at the time.
5. Using the PM method.
6. Less advance buying—more dependence on in-stock shoes.
7. Sales—catch bad guys before it’s too late and close out.
8. Buy as much good merchandise as you can at special prices
to help make up some markdowns.
9. Reducing opening buys and depending on fill-in service. PMs
for salespeople.
10. Buy more frequently, better buying, PMs on slow-moving
merchandise.
11. Careful buying at lowest prices. Cash on the buying line.
Buying closeouts, FDs, overstock, “cancellations.” (FD stands
for “factory-discontinued” style.)

3. 12. By buying less “chanceable” shoes. Buy only what you
need, watch sizes, don’t go overboard on new fads.
13. Buying more staple merchandise. Buying more from fewer
lines. Sticking with better nationally advertised merchandise.
14. No successful method with the current style situation.
Manufacturers are experimenting, the retailer takes the
markdowns—cuts gross profit by about 3 percent—keep your
stock at lowest level without losing sales.
4
Select a small sample of class members, work associates, or
friends and ask them to answer the following in a paragraph or
two: What are your career aspirations for the next five years?
Use one of the four basic units of content analysis to analyze
their responses. Describe your findings as frequencies for the
unit of analysis selected.
Bringing Research to Life
5
What data preparation process was Jason doing during data
entry?
6
Data entry followed data collection in the research profiled
during the opening vignette. What concerned Jason about this
process?
From Concept to Practice
7
Choose one of the cases from the text website that has an
instrument (check the Case Abstracts section for a listing of all
cases and an abstract for each). Code the instrument for data
entry.
From the Headlines
8
Your responses to the latest U.S. Census were used for two
purposes. First, the Census Bureau tallied each response to

4. produce an official population count. Second, it produced a 1-
in-20 sub-sample used for analysis by researchers. For those
younger than 65, the estimates from the sample are similar to
the full count. For those over age 65, the estimates disagree by
as much as 15 percent. The sample data suggest that there are
more very old men than very old women. And, the error jumbles
the correlation between age and employment, age and marital
status, and, possibly, other correlations as well. The Census
Bureau has refused to correct the data.
1. Should the data in the 1-in-20 micro-sample be used to study
people aged 65 and over?
2. What’s the source of the problem? Programming error,
coding error, or manipulating the data to protect the identity of
each individual?
Discussion Questions Chapter 16
Terms in Review
1
Define or explain:
1. Marginals.
2. Pareto diagram.
3. Nonresistant statistics.
4. Lower control limit.
5. The five-number summary.
Making Research Decisions
2
Suppose you were preparing two-way tables of percentages for

5. the following pairs of variables. How would you run the
percentages?
1. Age and consumption of breakfast cereal.
2. Family income and confidence about the family’s future.
3. Marital status and sports participation.
4. Crime rate and unemployment rate.
3
You study the attrition of entering college freshmen (those
students who enter college as freshmen but don’t stay to
graduate). You find the following relationships between
attrition, aid, and distance of home from college. What is your
interpretation? Consider all variables and relationships.
Aid
Home Near Receiving Aid
Home Far Receiving Aid
Yes (%)
No (%)
Yes (%)
No (%)
Yes (%)

6. No (%)
Drop Out
25
20
5
15
30
40
Stay
75
80
95
85
70
60
4
A local health agency is experimenting with two appeal letters,
A and B, with which to raise funds. It sends out 400 of the A
appeal and 400 of the B appeal (each subsample is divided

7. equally among working-class and middle-class neighborhoods).
The agency secures the results shown in the following table.
1. Which appeal is the best?
2. Which class responded better to which letter?
3. Is appeal or social class a more powerful independent
variable?
Appeal A
Appeal B
Middle Class (%)
Working Class (%)
Middle Class (%)
Working Class (%)
Contribution
20
40
15
30
No Contribution

8. 80
60
85
70
100
100
100
100
5
Assume you have collected data on sales associates of a large
retail organization in a major metropolitan area. You analyze
the data by type of work classification, education level, and
whether the workers were raised in a rural or urban setting. The
results are shown here. How would you interpret them?
Annual Retail Employee Turnover per 100 Employees
High Education
Low Education
Salaried

9. Hourly Wage
Salaried
Hourly Wage
Salaried
Hourly Wage
Rural
8
16
6
14
18
18
Urban
12
16
10
12
19

10. 20
Bringing Research to Life
6
Identify the variables being cross-tabulated by Sammye.
Identify some plausible reasons why such an exploration would
be a good idea.
From Concept to Practice
7
Use the data in Exhibit 16-5 to construct a stem-and-leaf
display.
1. Where do you find the main body of the distribution?
2. How many values reside outside the inner fence(s)?
From the Headlines
8
Asustek, the Taiwanese manufacturer that basically invented the
netbook category, has been researching more radical design
ideas, including a classy wrist-top computer, the Waveface
Ultra. It is made from a bendable display that can connect to the
Internet, make phone calls, and crunch data. Essentially, it’s a
bracelet that acts like a smartphone.
1. How might you use such a device to display stimuli for
respondents?
2. What is the interactive data exchange potential for
researchers?

11. Discussion Questions Chapter 17
Terms in Review
1
Distinguish between the following:
1. Parametric tests and nonparametric tests.
2. Type I error and Type II error.
3. Null hypothesis and alternative hypothesis.
4. Acceptance region and rejection region.
5. One-tailed tests and two-tailed tests.
6. Type II error and the power of the test.
2
Summarize the steps of hypothesis testing. What is the virtue of
this procedure?
3
In analysis of variance, what is the purpose of the mean square
between and the mean square within? If the null hypothesis is
accepted, what do these quantities look like?
4
Describe the assumptions for ANOVA, and explain how they
may be diagnosed.
Making Research Decisions
5
Suggest situations where the researcher should be more
concerned with Type II error than with Type I error.
1. How can the probability of a Type I error be reduced? A Type
II error?

12. 2. How does practical significance differ from statistical
significance?
3. Suppose you interview all the members of the freshman and
senior classes and find that 65 percent of the freshmen and 62
percent of the seniors favor a proposal to send Help Centers
offshore. Is this difference significant?
6
What hypothesis testing procedure would you use in the
following situations?
1. A test classifies applicants as accepted or rejected. On the
basis of data on 200 applicants, we test the hypothesis that ad
placement success is not related to gender.
2. A company manufactures and markets automobiles in two
different countries. We want to know if the gas mileage is the
same for vehicles from both facilities. There are samples of 45
units from each facility.
3. A company has three categories of marketing analysts: (1)
with professional qualifications but without work experience,
(2) with professional qualifications and with work experience,
and (3) without professional qualifications but with work
experience. A study exists that measures each analyst’s
motivation level (classified as high, normal, and low). A
hypothesis of no relation between analyst category and
motivation is to be tested.
4. A company has 24 salespersons. The test must evaluate
whether their sales performance is unchanged or has improved
after a training program.
5. A company has to evaluate whether it should attribute
increased sales to product quality, advertising, or an interaction
of product quality and advertising.

13. 7
You conduct a survey of a sample of 25 members of this year’s
graduating marketing students and find that the average GPA is
3.2. The standard deviation of the sample is 0.4. Over the last
10 years, the average GPA has been 3.0. Is the GPA of this
year’s students significantly different from the long-run
average? At what alpha level would it be significant?
8
You are curious about whether the professors and students at
your school are of different political persuasions, so you take a
sample of 20 professors and 20 students drawn randomly from
each population. You find that 10 professors say they are
conservative and 6 students say they are conservative. Is this a
statistically significant difference?
9
You contact a random sample of 36 graduates of Western
University and learn that their starting salaries averaged
$28,000 last year. You then contact a random sample of 40
graduates from Eastern University and find that their average
starting salary was $28,800. In each case, the standard deviation
of the sample was $1,000.
1. Test the null hypothesis that there is no difference between
average salaries received by the graduates of the two schools.
2. What assumptions are necessary for this test?
10
A random sample of students is interviewed to determine if
there is an association between class and attitude toward
corporations. With the following results, test the hypothesis that
there is no difference among students on this attitude.
Favorable
Neutral
Unfavorable

14. Freshmen
100
50
70
Sophomores
80
60
70
Juniors
50
50
80
Seniors
40
60
90
11
You do a survey of marketing students and liberal arts school
students to find out how many times a week they read a daily
newspaper. In each case, you interview 100 students. You find
the following:
m =
4.5 times per week
Sm =
1.5
la =
5.6 times per week
Sla =
2.0
Test the hypothesis that there is no significant difference
between these two samples.
12
One-Koat Paint Company has developed a new type of porch
paint that it hopes will be the most durable on the market. The

15. R&D group tests the new product against the two leading
competing products by using a machine that scrubs until it
wears through the coating. One-Koat runs five trials with each
product and secures the following results (in thousands of
scrubs):
Trial
One-Koat
Competitor A
Competitor B
1
37
34
24
2
30
19
25
3
34
22
23
4
28
31
20
5
29
27
20
Test the hypothesis that there are no differences between the
means of these products (a 5 .05).
13
A computer manufacturer is introducing a new product
specifically targeted at the home market and wishes to compare
the effectiveness of three sales strategies: computer stores,

16. home electronics stores, and department stores. Numbers of
sales by 15 salespeople are recorded here:
Electronics store: 5, 4, 3, 3, 3
Department store: 9, 7, 8, 6, 5
Computer store: 7, 4, 8, 4, 3
1. Test the hypothesis that there is no difference between the
means of the retailers (α = .05).
2. Select a multiple comparison test, if necessary, to determine
which groups differ in mean sales (α = .05).
From the Headlines
14
Researchers at the University of Aberdeen found that when
people were asked to recall past events or imagine future ones,
the participants’ bodies subliminally acted out the metaphors we
commonly conceptualized with the flow of time. With past
years, the participants leaned backward, while when imagining
the future, they leaned forward. The leanings were small, but
the directionality was clear and dependable. Using this research
as a base, if you have two groups (group A holds a cup of hot
coffee, and group B holds iced coffee), what statistical
hypothesis would you propose to test the groups’ perceptions of
the personality of an imaginary individual holding coffee based
on its temperature?
Your LSI Styles Profile
The raw and percentile scores in the table below and the
extensions on the circumplex shown below depict your
perceptions of how you think and behave.
The CONSTRUCTIVE Styles (11, 12, 1, and 2 o'clock
positions) reflect self-enhancing thinking and behavior that
contribute to one's level of satisfaction, ability to develop

17. healthy relationships and work effectively with people, and
proficiency at accomplishing tasks.
The PASSIVE/DEFENSIVE Styles (3, 4, 5, and 6 o'clock
positions) represent self-protecting thinking and behavior that
promote the fulfillment of security needs through interaction
with people.
The AGGRESSIVE/DEFENSIVE Styles (7, 8, 9, and 10 o'clock
positions) describe self-promoting thinking and behavior used
to maintain status/position and fulfill security needs through
task-related activities.
Position
Style
Score
Percentile
1
Humanistic-Encouraging
39
96
2
Affiliative
37
90
3
Approval
9
25
4
Conventional
21
87
5
Dependent
9
15
6
Avoidance

18. 9
70
7
Oppositional
3
18
8
Power
4
34
9
Competitive
10
34
10
Perfectionistic
17
32
11
Achievement
36
80
12
Self-Actualizing
36
90
The raw scores potentially range from 0 to 40. The percentile
scores represent your results compared to those of 9,207
individuals who previously completed the Life Styles Inventory.
For example, a percentile score of 75 means that you scored
higher along a particular position than 75% of the other
respondents in the sample and, in turn, indicates that the style
represented by that position is strongly descriptive of you. In
contrast, a score of 25 means that you scored higher than only
about 25% of the other respondents and therefore indicates that
the style represented by that position is not very descriptive of

19. you.
Your LSI Styles Circumplex
For detailed descriptions of each of these 12 styles,
click on the circumplex graphic in each of the 12 sections.
Examining your Circumplex
To accurately interpret your LSI results, it is important for you
to consider your score on each style in terms of its range (high,
medium, or low) on the profile. The three ranges correspond to
the percentile points in the circumplex and in the table above.