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Textbook
Business Statistics: For Contemporary Decision Making, 7th EditionOctober 2011, ©2012
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1. Introduction to Statistics 02
2. Charts and Graphs 18
3. Descriptive Statistics 52
4. Probability 98
UNIT II DISTRIBUTIONS AND SAMPLING
5. Discrete Distributions 142
6. Continuous Distributions 184
7. Sampling and Sampling Distributions 222
UNIT III MAKING INFERENCES ABOUT POPULATION PARAMETERS
8. Statistical Inference: Estimation for Single Populations 256
9. Statistical Inference: Hypothesis Testing for Single Populations 294
10. Statistical Inferences about Two Populations 348
11. Analysis of Variance and Design of Experiments 408
UNIT IV REGRESSION ANALYSIS AND FORECASTING
12. Simple Regression Analysis and Correlation 470
13. Multiple Regression Analysis 522
14. Building Multiple Regression Models 552
15. Time-Series Forecasting and Index Numbers 602
UNIT V NONPARAMETRIC STATISTICS AND QUALITY
16. Analysis of Categorical Data 658
17. Nonparametric Statistics 684
18. Statistical Quality Control 734
APPENDICES
A. Tables 779
B. Answers to Selected Odd-Numbered Quantitative Problems 819
GLOSSARY 829
INDEX 839
The following materials are available at www.wiley.com/college/black
19. Decision Analysis C19-2
Supplement 1. Summation Notation S1-1
Supplement 2. Derivation of Simple Regression Formulas for Slope and y Intercept S2-1
Supplement 3. Advanced Exponential Smoothing S3-1
• NEW and Improved Visuals: Graphs, tables, and figures have been added throughout the text to illustrate and underscore concepts.
• NEW Cases: New, current and relevant businesses are profiled to help students connect real organizations with business statistics concepts.
• Decision Dilemma & Decision Dilemma Solved: Chapter-opening vignettes are brief business-world scenarios which use the techniques introduced in the chapter to solve a business decision dilemma; at the end of chapters, dilemmas are addressed to reinforce the chapter concept.
• Ethical Considerations: A feature in each chapter, Ethical Considerations integrate the topic of ethics with applications of business statistics.
• Tree Taxonomy Diagrams: Further illustrate the connection between topics and techniques and the ability to see the big picture of inferential statistics.






