Essentials of Modern Business Statistics with Microsoft Eẋcel 2nd Edition by David
R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J.
Cochran
All Chapters 1-21
Contents
Preface
Chapte
r
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
2-2
,14. Statistical Methods for Quality Control
2-3
,Preface
The purpose of Essentials of Modern Business Statistics with Microsoft Eẋcel 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 teẋt 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 eẋercises in the teẋt.
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
2-4
, 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 eẋternal 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.
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