Essentials of Modern
Business Statistics
With Microsoft Excel
Second Edition
David R. Anderson
University of Cincinnati
Dennis J. Sweeney
University of Cincinnati
Thomas A. Williams
Rochester Institute of Technology
South-Western
Cincinnati, Ohio
2-1
,Contents
Preface
Chapter
1. Data and Statistics
2. Descriptive Statistics: Tabular and Graphical Methods
3. Descriptive Statistics: Numerical Methods
4. Introduction to Probability
5. Discrete Probability Distributions
6. Continuous Probability Distributions
7. Sampling and Sampling Distributions
8. Interval Estimation
9. Hypothesis Testing
10. Comparisons Involving Means
11. Comparisons Involving Proportions and A Test of Independence
12. Simple Linear Regression
13. Multiple Regression
14. Statistical Methods for Quality Control
2-2
,Preface
The purpose of Essentials of Modern Business Statistics with Microsoft Excel 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
2-3
, 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. Understand that data are obtained using one of the following scales of measurement: nominal,
ordinal, interval, and ratio.
4. Obtain an understanding of the difference between qualitative, quantitative, crossectional and time
series data.
5. Learn about the sources of data for statistical analysis both internal and external to the firm.
6. Be aware of how errors can arise in data.
7. Know the meaning of descriptive statistics and statistical inference.
8. Be able to distinguish between a population and a sample.
9. Understand the role a sample plays in making statistical inferences about the population.
2-4
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