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

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:

Chapter 1
1 - 2
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

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Chapter 1
1 - 4
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

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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%

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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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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

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