Business Statistics: For Contemporary Decision Making

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The sixth edition helps business professionals see the big picture in the application of business statistics. It includes the Tree Taxonomy Diagram for Unit 3, which illustrates the connection between topics and helps them pick the correct technique to use to solve problems. A new organization of the chapters also makes the material easier to learn. And additional real-world examples are included as well to make the concepts more relevant. Business professionals will be able to apply this information in order to make the most effective decisions. About The Author Ken Black is currently Professor of Decision Sciences in the School of Business and Public Administration at the University of Houston-Clear Lake. Born in Cambridge, Massachusetts and raised in Missouri, he earned a Bachelor's degree in mathematics from Graceland College, a Master's degree in math education from the University of Texas at El Paso, a Ph.D. in business administration in management science, and a Ph.D. in educational research from the University of North Texas. Since joining the faculty in 1979, Professor Black has taught all levels of statistics courses, forecasting, management science, market research, and production/operations management. He published fifteen journal articles and over twenty professional papers, as well as two textbooks: Business Statistics: An Introductory Course and Business Statistics: Contemporary Decision Making. Table of Contents Unit I: Introduction. Chapter 1 Introduction to Statistics. Chapter 2 Charts and Graphs. Chapter 3 Descriptive Statistics. Chapter 4 Probability. Unit II: Distributions and Sampling. Chapter 5 Discrete Distributions. Chapter 6 Continuous Distributions. Chapter 7 Sampling and Sampling Distributions. Unit III: Making Inferences about Population Parameters. Chapter 8 Statistical Inference: Estimation for Single Populations. Chapter 9 Statistical Inference: Hypothesis Testing for Single Populations. Chapter 10 Statistical Inferences about Two Populations. Chapter 11 Analysis of Variance and Design of Experiments. Chapter 12 Analysis of Categorical Data. Chapter 13 Nonparametric Statistics. Unit IV: Regression, Forecasting, and Quality: Relationships, Prediction, and Process Improvement. Chapter 14 Simple Regression Analysis. Chapter 15 Multiple Regression Analysis. Chapter 16 Building Multiple Regression Models. Chapter 17 Time-Series Forecasting and Index Numbers. Chapter 18 Statistical Quality Control. Appendix A Tables. Appendix B Answers to Selected Odd-Numbered Quantitative Problems. Glossary. Index. The following materials are available at: www.wiley.com/college/black Chapter 19 Decision Analysis. Supplement 1 Summation Notation. Supplement 2 Derivation of Simple Regression Formulas for Slope and y Intercept. Supplement 3 Advanced Exponential Smoothing.