Answer the Terms in Review, Making Research Decisions, Bringing Research to Life, Concept to Practice and From the Headlines for Chapters 15, 16, and 17. See attachment
I need it no later than 0600am 5 Nov 13 eastern time
Discussion
Questions Chapter 15
Terms in Review
1
Define or explain:
Coding rules.
Spreadsheet data entry.
Bar codes.
Precoded instruments.
Content analysis.
Missing data.
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.
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.)
Using PMs before too old.
Also reducing price during season. Holding meetings with salespeople
indicating which shoes to push.
By putting PMs on any
slow-selling items and promoting same. More careful check of shoes
purchased.
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.
Using the PM method.
Less advance buying—more
dependence on in-stock shoes.
Sales—catch bad guys before
it’s too late and close out.
Buy as much good merchandise
as you can at special prices to help make up some markdowns.
Reducing opening buys and
depending on fill-in service. PMs for salespeople.
Buy more frequently, better
buying, PMs on slow-moving merchandise.
Careful buying at lowest
prices. Cash on the buying line. Buying closeouts, FDs, overstock,
“cancellations.” (FD stands for “factory-discontinued” style.)
By buying less “chanceable”
shoes. Buy only what you need, watch sizes, don’t go overboard on new
fads.
Buying more staple
merchandise. Buying more from fewer lines. Sticking with better nationally
advertised merchandise.
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 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.
Should the data in the
1-in-20 micro-sample be used to study people aged 65 and over?
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:
Marginals.
Pareto diagram.
Nonresistant statistics.
Lower control limit.
The five-number summary.
Making Research Decisions
2
Suppose you were preparing
two-way tables of percentages for the following pairs of variables. How
would you run the percentages?
Age and consumption of
breakfast cereal.
Family income and
confidence about the family’s future.
Marital status and sports
participation.
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 (%)
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 equally among working-class and middle-class neighborhoods). The
agency secures the results shown in the following table.
Which appeal is the best?
Which class responded
better to which letter?
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
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
Hourly Wage
Salaried
Hourly Wage
Salaried
Hourly Wage
Rural
8
16
6
14
18
18
Urban
12
16
10
12
19
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.
Where do you find the main
body of the distribution?
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.
How might you use such a
device to display stimuli for respondents?
What is the interactive
data exchange potential for researchers?
Discussion
Questions Chapter 17
Terms in Review
1
Distinguish between the following:
Parametric
tests and nonparametric tests.
Type
I error and Type II error.
Null
hypothesis and alternative hypothesis.
Acceptance
region and rejection region.
One-tailed
tests and two-tailed tests.
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.
How
can the probability of a Type I error be reduced? A Type II error?
How
does practical significance differ from statistical significance?
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?
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.
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.
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.
A
company has 24 salespersons. The test must evaluate whether their sales
performance is unchanged or has improved after a training program.
A
company has to evaluate whether it should attribute increased sales to
product quality, advertising, or an interaction of product quality and
advertising.
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.
Test
the null hypothesis that there is no difference between average salaries
received by the graduates of the two schools.
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
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 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, 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
Test
the hypothesis that there is no difference between the means of the
retailers (α = .05).
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?
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