Statistics for Business
and Economics
Eighth Edition
David R. Anderson
University of Cincinnati
Dennis J. Sweeney
University of Cincinnati
Thomas A. Williams
Rochester Institute of Technology
2002 by South-Western/Thomson Learning
Cincinnati, Ohio
,Contents
Chapter
1. Data and Statistics
2. Descriptive Statistics: Tabular and Graphical Approaches
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. Statistical Inference about Means and Proportions With Two Populations
11. Inferences about Population Variances
12. Tests of Goodness of Fit and Independence
13. Analysis of Variance and Experimental Design
14. Simple Linear Regression
15. Multiple Regression
16. Regression Analysis: Model Building
17. Index Numbers
18. Forecasting
19. Nonparametric Methods
20. Statistical Methods for Quality Control
21. 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.
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
, 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 qualitative, 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.
1-1