Solution Manual for Statistics for Business and Economics, 11th Edition

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Solutions Manual to Accompany
Statistics for Business
and Economics
Eleventh Edition
David R. Anderson
University of Cincinnati
Dennis J. Sweeney
University of Cincinnati
Thomas A. Williams
Rochester Institute of Technology

Contents
Chapter
1. Data and Statistics
2. Descriptive Statistics: Tabular and Graphical Presentations
3. Descriptive Statistics: Numerical Measures
4. Introduction to Probability
5. Discrete Probability Distributions
6. Continuous Probability Distributions
7. Sampling and Sampling Distributions
8. Interval Estimation
9. Hypothesis Testing
10. Statistical Inference about Means and Proportions With Two Populations
11. Inferences about Population Variances
12. Tests of Goodness of Fit and Independence
13. Experimental Design and Analysis of Variance
14. Simple Linear Regression
15. Multiple Regression
16. Regression Analysis: Model Building
17. Index Numbers
18. Time Series Analysis and Forecasting
19. Nonparametric Methods
20. Statistical Methods for Quality Control
21. Decision Analysis
22. Sample Survey

Preface
The purpose of Statistics for Business and Economics is to provide students, primarily in
the fields of business administration and economics, with a sound conceptual introduction
to the field of statistics and its many applications. The text is applications-oriented and has
been written with the needs of the nonmathematician in mind.
The solutions manual furnishes assistance by identifying learning objectives and providing
detailed solutions for all exercises in the text.
Note: The solutions to the case problems are included in a separate manual.
Acknowledgements
We would like to provide special recognition to Catherine J. Williams for her efforts in
preparing the solutions manual.
David R. Anderson
Dennis J. Sweeney
Thomas A. Williams

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1 - 1
Chapter 1
Data and Statistics
Learning Objectives
1. Obtain an appreciation for the breadth of statistical applications in business and economics.
2. Understand the meaning of the terms elements, variables, and observations as they are used in
statistics.
3. Obtain an understanding of the difference between categorical, quantitative, crossectional and time
series data.
4. Learn about the sources of data for statistical analysis both internal and external to the firm.
5. Be aware of how errors can arise in data.
6. Know the meaning of descriptive statistics and statistical inference.
7. Be able to distinguish between a population and a sample.
8. Understand the role a sample plays in making statistical inferences about the population.
9. Know the meaning of the term data mining.
10. Be aware of ethical guidelines for statistical practice.
Solutions:

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Chapter 1
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1. Statistics can be referred to as numerical facts. In a broader sense, statistics is the field of study
dealing with the collection, analysis, presentation and interpretation of data.
2. a. The ten elements are the ten cars
b. 5 variables: Size, Cylinders, City MPG, Highway MPG, and Fuel
c. Categorical variables: Size and Fuel
Quantitative variables: Cylinders, City MPG, and Highway MPG
d.
Variable Measurement Scale
Size Ordinal
Cylinders Ratio
City MPG Ratio
Highway MPG Ratio
Fuel Nominal
3. a. Average mpg for city driving = 182/10 = 18.2 mpg
b. Average mpg for highway driving = 261/10 = 26.1 mpg
On average, the miles per gallon for highway driving is 26.1 – 18.2 = 7.9 mpg greater compared to
city driving.
c. 3 of 10 or 30% have four cylinder engines
d. 6 of 10 or 60% use regular fuel
4. a. The seven elements are the seven schools shown
b. 5 variables: State, Campus Setting, Endowment, Applicants Admitted, and NCAA Division
c. Categorical variables: State, Campus Setting, and NCAA Division
Quantitative variables: Endowment and Applicants Admitted
5. a. Average endowment = 74.6/7 = $10.657 billion
b. Average percentage admitted = 111/7 = 15.86%
c. 3 of 7 or 42.9% have NCAA Division III varsity teams
d. 3 of 7 or 42.9% have a City: Midsize campus setting
6. a. Quantitative
b. Categorical
c. Categorical
d. Quantitative

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Data and Statistics
1 - 3
e. Categorical
7. a. Although the data are recorded as numbers, the numbers are codes for the ratings of Fair (1),
Average (2), Good (3) and Excellent (4). Thus the variables are categorical with each data value
corresponding to a rating category for the variable.
b. The data may also be ranked in order of the quality. A higher number indicates a higher rating on a
scale from Fair (1) to Excellent (4). Since the data can be ranked or ordered, the scale of
measurement is ordinal.
8. a. 1015
b. Categorical
c. Percentages
d. .10(1015) = 101.5
101 or 102 respondents said the Federal Bank is doing a good job.
9. a. Categorical
b. 30 of 71; 42.3%
10. a. Quantitative; ratio scale of measurement
b. Categorical; nominal scale of measurement
c. Categorical; ordinal scale of measurement since the responses can be ordered from earliest (high
school) to latest (retirement)
d. Quantitative; ratio scale of measurement
e. Categorical; nominal scale of measurement
11. a. Quantitative; ratio
b. Categorical; ordinal
c. Categorical; ordinal (assuming employees can be ranked by classification)
d. Quantitative; ratio
e. Categorical; nominal
12. a. The population is all visitors coming to the state of Hawaii.
b. Since airline flights carry the vast majority of visitors to the state, the use of questionnaires for
passengers during incoming flights is a good way to reach this population. The questionnaire
actually appears on the back of a mandatory plants and animals declaration form that passengers
must complete during the incoming flight. A large percentage of passengers complete the visitor
information questionnaire.
c. Questions 1 and 4 provide quantitative data indicating the number of visits and the number of days
in Hawaii. Questions 2 and 3 provide categorical data indicating the categories of reason for the trip
and where the visitor plans to stay.

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Chapter 1
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13. a. Federal spending measured in trillions of dollars
b. Quantitative
c. Time series
d. Federal spending has increased over time
14. a.0
2
4
6
8
10
12
2003 2004 2005 2006 2007 2008
Year
Vehicles (millions)
Toyota
GM
Ford
DC
b. According to the CSM data, Toyota surpasses General Motors as the biggest auto manufacturer in
the world in 2006. In 2006, Toyota manufactured approximately (9.1 – 8.9) = .2 million or 200,000
more vehicles than General Motors. The gap is expected to widen to 800,000 vehicles in 2007.
General Motors is the only manufacturer showing a decline in vehicle production over the four year
period.
c. The following is a bar chart of cross-sectional data as it shows the number of vehicles manufactured
in 2007.

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Data and Statistics
1 - 50
2
4
6
8
10
12
GM Ford DC Toyota
Manufacturer
Vehicles (millions)
15. a. Quantitative – number of new drugs approved
b. Time series from 1996 to 2003
c. 18
d. 2002; 16 new drugs
e. Over the eight-year period, the number of new drugs approved by the FDA declined. From
approximately 50 new drugs approved in 1996, the most recent years are showing only 16 to 18 new
drugs approved.
16. The answer to this exercise depends upon the time series of the average price per gallon of
conventional regular gasoline since April 2009. Contact the website www.eia.doe.gov to obtain the
more recent time series data. In the spring of 2009, the average price per gallon was once again
increasing. A continuation of the usual summer peak in gasoline prices was anticipated.
17. Internal data on salaries of other employees can be obtained from the personnel department.
External data might be obtained from the Department of Labor or industry associations.
18. a.155 .36
430 = or 36%
b. 44% of 430 = .44(430) = 189 business travelers
c. Categorical data with categories online travel site, travel agent, direct with airline/hotel, other.
19. a. All subscribers of Business Week in North America at the time the survey was conducted.
b. Quantitative
c. Categorical (yes or no)
d. Crossectional - all the data relate to the same time.

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Chapter 1
1 - 6
e. Using the sample results, we could infer or estimate 59% of the population of subscribers have an
annual income of $75,000 or more and 50% of the population of subscribers have an American
Express credit card.
20. a. 43% of managers were bullish or very bullish.
21% of managers expected health care to be the leading industry over the next 12 months.
b. We estimate the average 12-month return estimate for the population of investment managers to be
11.2%.
c. We estimate the average over the population of investment managers to be 2.5 years.
21. a. The two populations are the population of women whose mothers took the drug DES during
pregnancy and the population of women whose mothers did not take the drug DES during
pregnancy.
b. It was a survey.
c. 63 / 3.980 = 15.8 women out of each 1000 developed tissue abnormalities.
d. The article reported “twice” as many abnormalities in the women whose mothers had taken DES
during pregnancy. Thus, a rough estimate would be 15.8/2 = 7.9 abnormalities per 1000 women
whose mothers had not taken DES during pregnancy.
e. In many situations, disease occurrences are rare and affect only a small portion of the population.
Large samples are needed to collect data on a reasonable number of cases where the disease exists.
22. a. The population consists of all customers of the chain’s stores in Charlotte, North Carolina.
b. Some of the ways that could used to collect the data are as follows:
• Customers entering or leaving the store could be surveyed
• A survey could be mailed to customers who have a shopper’s club card for the stores
• Customers could be given a printed survey when they check out
• Customers could be given a coupon that asks them to complete a brief on-line survey; if they do,
they will receive a 5% discount on their next shopping trip.
23. a. Nielsen is attempting to measure the popularity of each television program by showing the
percentage of households that are watching the program.
b. All households with televisions in the United States.
c. A census of the population is impossible. A sample provides timely information in that the ratings
and share data can be obtained weekly. In addition, the sample saves data collection costs.
d. The cancellation or renewal of television programs, advertising cost rates for the television programs
and the scheduling of television programs are often based on the Nielsen information.
24. a. This is a statistically correct descriptive statistic for the sample.
b. An incorrect generalization since the data was not collected for the entire population.
c. An acceptable statistical inference based on the use of the word “estimate.”

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Data and Statistics
1 - 7
d. While this statement is true for the sample, it is not a justifiable conclusion for the entire population.
e. This statement is not statistically supportable. While it is true for the particular sample observed, it
is entirely possible and even very likely that at least some students will be outside the 65 to 90 range
of grades.
25. a. There are five variables: Exchange, Ticker Symbol, Market Cap, Price/Earnings Ratio and Gross
Profit Margin.
b. Categorical variables: Exchange and Ticker Symbol
Quantitative variables: Market Cap, Price/Earnings Ratio, Gross Profit Margin
c. Exchange variable:
Exchange Frequency Percent Frequency
AMEX 5 (5/25) 20%
NYSE 3 (3/25) 12%
OTC 17 (17/25) 68%
250
10
20
30
40
50
60
70
80
AMEX NYSE OTC
Exchange
Percent Frequency
d. Gross Profit Margin variable:
Gross Profit Margin Frequency
0.0 – 14.9 2
15.0 – 29.9 6
30.0 – 44.9 8
45.0 – 59.9 6
60.0 – 74.9 3

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2 - 1
Chapter 2
Descriptive Statistics: Tabular and
Graphical Presentations
Learning Objectives
1. Learn how to construct and interpret summarization procedures for qualitative data such as:
frequency and relative frequency distributions, bar graphs and pie charts.
2. Learn how to construct and interpret tabular summarization procedures for quantitative data such as:
frequency and relative frequency distributions, cumulative frequency and cumulative relative
frequency distributions.
3. Learn how to construct a dot plot, a histogram, and an ogive as graphical summaries of quantitative
data.
4. Learn how the shape of a data distribution is revealed by a histogram. Learn how to recognize when
a data distribution is negatively skewed, symmetric, and positively skewed.
5. Be able to use and interpret the exploratory data analysis technique of a stem-and-leaf display.
6. Learn how to construct and interpret cross tabulations and scatter diagrams of bivariate data.

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Chapter 2
2 - 4
d. CSI had the largest viewing audience. Desperate Housewives was in second place.
5. a.
Name Frequency Relative Frequency Percent Frequency
Brown 7 .14 14%
Davis 6 .12 12%
Johnson 10 .20 20%
Jones 7 .14 14%
Smith 12 .24 24%
Williams 8 .16 16%
50 1.00
b.0
2
4
6
8
10
12
14
Brown Davis Johnson Jones Smith Williams
Name
Frequency
c. Brown .14 x 360 = 50.4
Davis .12 x 360 = 43.2
Johnson .20 x 360 = 72.0
Jones .14 x 360 = 50.4
Smith .24 x 360 = 86.4
Williams .16 x 360 = 57.6L&O
20%
CSI
36%
Trace
18%
Housewives
26%

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Descriptive Statistics: Tabular and Graphical Presentations
2 - 5
d. Most common: Smith, Johnson and Williams
6. a.
Network Frequency Percent Frequency
ABC 15 30%
CBS 17 34%
FOX 1 2%
NBC 17 34%
Total 50 100%0
2
4
6
8
10
12
14
16
18
ABC CBS FOX NBC
Network
Frequency
b. CBS and NBC are tied, each with 17 of the top rated television shows. ABC is a close third with 15.
The fact that the three networks are so close is surprising. FOX, the newest television network, does
not have the history to compete with the other three networks in term of the top rated shows in
television history.Williams
16%
Brown
14%
Davis
12%
Johnson
20%
Jones
14%
Smith
24%

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Chapter 2
2 - 6
7.
Rating Frequency Relative Frequency
Outstanding 19 0.38
Very Good 13 0.26
Good 10 0.20
Average 6 0.12
Poor 2 0.04
50 1.00
Management should be pleased with these results. 64% of the ratings are very good to outstanding.
84% of the ratings are good or better. Comparing these ratings with previous results will show
whether or not the restaurant is making improvements in its ratings of food quality.
8. a.
Position Frequency Relative Frequency
Pitcher 17 0.309
Catcher 4 0.073
1st Base 5 0.091
2nd Base 4 0.073
3rd Base 2 0.036
Shortstop 5 0.091
Left Field 6 0.109
Center Field 5 0.091
Right Field 7 0.127
55 1.000
b. Pitchers (Almost 31%)
c. 3rd Base (3 - 4%)
d. Right Field (Almost 13%)
e. Infielders (16 or 29.1%) to Outfielders (18 or 32.7%)
9. a.
b. Where do you live now?
Living Area Live Now Ideal Community
City 32% 24%
Suburb 26% 25%
Small Town 26% 30%
Rural Area 16% 21%
Total 100% 100%

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Descriptive Statistics: Tabular and Graphical Presentations
2 - 7
What do you consider the ideal community?
c. Most adults are now living in a city (32%).
d. Most adults consider the ideal community a small town (30%).
e. Percent changes by living area: City -8%, Suburb -1%, Small Town +4%, and Rural Area +5%.
Suburb living is steady, but the trend would be that living in the city would decline while
living in small towns and rural areas would increase.
10. a.
Rating Frequency
Excellent 20
Good 101
Fair 528
Bad 244
Terrible 122
Total 1015
b.

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Chapter 2
2 - 8
Rating
Percent
Frequency
Excellent 2
Good 10
Fair 52
Bad 24
Terrible 12
Total 100
c.
d. 24% + 12% = 36% of adults in the United Sates think the Federal Bank is doing a bad or a terrible
job in handling the credit problems. Only 10% + 2% = 12% think the Federal Bank is doing a good
or excellent job.
e. 40% + 10% = 50% of adults in Spain think the European Central Bank is doing a bad or terrible job
in handling the credit problems. Only 4% of adults in Spain think the European Central Bank is
doing a good or excellent job.
Both countries show pessimism and relatively low confidence in how the banks are handling the
credit problems in the financial markets. But in comparing the two countries, adults in Spain show
more concern and more pessimism about the bank’s ability compared to adults in the United States.
11.
Class Frequency Relative Frequency Percent Frequency
12-14 2 0.050 5.0
15-17 8 0.200 20.0
18-20 11 0.275 27.5
21-23 10 0.250 25.0
24-26 9 0.225 22.5
Total 40 1.000 100.0
12.
Class Cumulative Frequency Cumulative Relative Frequency

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Chapter 2
2 - 10
Class Frequency Percent Frequency
6.0 - 7.9 4 20
8.0 - 9.9 2 10
10.0 - 11.9 8 40
12.0 - 13.9 3 15
14.0 - 15.9 3 15
20 100
15. a/b.
Waiting Time Frequency Relative Frequency
0 - 4 4 0.20
5 - 9 8 0.40
10 - 14 5 0.25
15 - 19 2 0.10
20 - 24 1 0.05
Totals 20 1.00
c/d.
Waiting Time Cumulative Frequency Cumulative Relative Frequency
Less than or equal to 4 4 0.20
Less than or equal to 9 12 0.60
Less than or equal to 14 17 0.85
Less than or equal to 19 19 0.95
Less than or equal to 24 20 1.00
e. 12/20 = 0.60
16. a.
Salary Frequency
150-159 1
160-169 3
170-179 7
180-189 5
190-199 1
200-209 2
210-219 1
Total 20
b.
Salary
Percent
Frequency
150-159 5
160-169 15
170-179 35
180-189 25
190-199 5
200-209 10
210-219 5
Total 100
c.
Salary
Cumulative Percent
Frequency

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Descriptive Statistics: Tabular and Graphical Presentations
2 - 11
Less than or equal to 159 5
Less than or equal to 169 20
Less than or equal to 179 55
Less than or equal to 189 80
Less than or equal to 199 85
Less than or equal to 209 95
Less than or equal to 219 100
Total 100
d.
e. There is skewness to the right.
f. (3/20)(100) = 15%
17. a. The highest price stock is for IBM with a price of $107 per share.
The lowest price stock is for Alcoa with a price of $11 per share.
b. A class size of 10 results in 10 classes.
Price per Share Frequency
$10-19 5
$20-29 10
$30-39 3
$40-49 2
$50-59 6
$60-69 2
$70-79 1
$80-89 0
$90-99 0
$100-109 1
c.

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Chapter 2
2 - 12
The general shape of the distribution is skewed to the right. Half of the companies (15) have a price
per share less than $30. A mid-priced stock appears to be in the $30 to $49 range, while the most
frequently priced stock is in the $20 to $29 range.
Five stocks are less than $20 per share (Alcoa, Bank of America, General Electric, Intel and Pfizer).
Four stocks are $60 or more per share (3M, Chevron, ExxonMobil and IBM).
d. A variety of comparisons are possible depending upon when the study is done.
18. a. The lowest holiday spending is $180; the highest $2050.
b.
Spending Frequency Percent
0-249 3 12
250-499 6 24
500-749 5 20
750-999 5 20
1000-1249 3 12
1250-1499 1 4
1500-1759 0 0
1750-1999 1 4
2000-2249 1 4
Total 25 100
c. The distribution shows a positive skewness.

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Descriptive Statistics: Tabular and Graphical Presentations
2 - 130
1
2
3
4
5
6
7
0-249 250-499 500-749 750-999 1000-
1249
1250-
1499
1500-
1759
1750-
1999
2000-
2249
Holiday Spending
Frequency
d. The holiday spending ranges from $0 to less than $2250. The majority of the spending is between
$250 and $1000 with 16 of the 25 customers, 64%, in this range. The middle or average spending is around
$750 per customer. The distribution has a positive skewness with two consumers above $1750. One consumer
is above $2000.
19. a/b/c/d.
Class
(Minutes) Frequency
Relative
Frequency
Cumulative
Frequency
Cumulative Relative
Frequency
1-5 12 .60 12 .60
6-10 3 .15 15 .75
11-15 2 .10 17 .85
16-20 1 .05 18 .90
21-25 1 .05 19 .95
26-30 0 .00 19 .95
31-34 1 .05 20 1.00
e.
f. 60% of office workers spend 5 minutes or less on unsolicited email and spam. However, 25% of
office workers spend more than 10 minutes per day on this task.
20. a.
Off-Course Income Percent0
0.2
0.4
0.6
0.8
1
0 5 10 15 20 25 30 35
Time

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Chapter 2
2 - 14
($1000s) Frequency Frequency
0-4,999 30 60
5,000-9,999 9 18
10,000-14,999 4 8
15,000-19,999 0 0
20,000-24,999 3 6
25,000-29,999 2 4
30,000-34,999 0 0
35000-39,999 0 0
40,000-44,999 1 2
45,000-49,999 0 0
Over 50,000 1 2
Total 50 100
b. Histogram of Off-Course Income
Note: The first class is labeled 5000 and provides the golfers who had an off-course income in the
range 0 to 4999 or less than 5000. These were the golfers with less than $5 million in off-course
income.
c. Off-course income is skewed to the right. Only Tiger Woods earns over $50 million.
d. Considering the top 50 golfers, the majority (60%) earn less than $5 million in off-course income per
year. 60% + 18% = 78% earn less than $10 million. Five golfers (10%) earn between $20 million
and $30 million. Tiger Woods with $99.8 million and Phil Mickelson with $40.2 million in off-
course income are clearly the leaders in this income category.
21. a/b.

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Descriptive Statistics: Tabular and Graphical Presentations
2 - 15
Computer
Usage (Hours) Frequency
Relative
Frequency
0.0 - 2.9 5 0.10
3.0 - 5.9 28 0.56
6.0 - 8.9 8 0.16
9.0 - 11.9 6 0.12
12.0 - 14.9 3 0.06
Total 50 1.00
c.0
5
10
15
20
25
30
0-2.9 3-5.9 6-8.9 9-11.9 12-14.9
Computer Usage (Hours)
Frequency
d.
e. The majority of the computer users are in the 3 to 6 hour range. Usage is somewhat skewed toward
the right with 3 users in the 12 to 14.9 hour range.
22.

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Descriptive Statistics: Tabular and Graphical Presentations
2 - 17
1 0 3 7 7
2 4 5 5
3 0 0 5 5 9
4 0 0 0 5 5 8
5 0 0 0 4 5 5
This stem-and-leaf display shows that the trading prices are closely grouped together. Rotating the
stem-and-leaf display counter clockwise shows a histogram that is slightly skewed to the left but is
roughly symmetric.
b. 500 shares traded online at $50 per share.
0 5 7
1 0 1 1 3 4
1 5 5 5 8
2 0 0 0 0 0 0
2 5 5
3 0 0 0
3 6
4
4
5
5
6 3
This stretched stem-and-leaf display shows that the distribution of online trading prices for most of
the brokers for 500 shares are lower than the trading prices for broker assisted trades of 100 shares.
There are a couple of outliers. York Securities charges $36 for an online trade and Investors National
charges much more than the other brokers: $62.50 for an online trade.
27. a.
7 5 9
8 3 6
9 5 6 8
10 0 4 4
11 1 5
12
13 7
14 5 5
b. Observations such as the following can be made using the stem-and-leaf display.

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Chapter 2
2 - 18
• The daily rate varies from $75 to $145
• Typical mid-priced daily rates are $95 to $115 with the average daily rate around $100.
• A daily rate in excess of $115 should be considered relatively high. High daily rates of $137 and
$145 were found at three ski resorts.
28. a.
2 1 4
2 6 7
3 0 1 1 1 2 3
3 5 6 7 7
4 0 0 3 3 3 3 3 4 4
4 6 6 7 9
5 0 0 0 2 2
5 5 6 7 9
6 1 4
6 6
7 2
b. Most frequent age group: 40-44 with 9 runners
c. 43 was the most frequent age with 5 runners
d. 4/40 = 10% of the runners were “20-something.” With only 10% of the registrants “20-something,”
the article pointed out that surprisingly few registrants were in this age group. One suggested reason
was that “20-somethings” don’t have the time to train for a 13.1 mile race. For “20-somethings,”
college, starting careers, and starting families may take priority over training for long distance races.
29. a.y
x
A
B
C
5
11
2
0
2
10
1218
5
13
12
30
Total1 2
Total
b.

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Descriptive Statistics: Tabular and Graphical Presentations
2 - 19y
x
A
B
C
100.0
84.6
16.7
1
0.0
15.4
83.3
2
100.0
100.0
100.0
Total
c.y
x
A
B
C
27.8
61.1
11.1
100.0
0.0
16.7
83.3
100.0
1 2
Total
d. Category A values for x are always associated with category 1 values for y. Category B values for x
are usually associated with category 1 values for y. Category C values for x are usually associated
with category 2 values for y.
30. a.-40
-24
-8
8
24
40
56
-40 -30 -20 -10 0 10 20 30 40
x
y
b. There is a negative relationship between x and y; y decreases as x increases.

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