Synopses & Reviews
Measures of Dispersion. Additional Dispersion. Descriptive Statistics from Grouped Data. Statistical Measures of Association. Summary. 4. Data Collection and Sampling Methods. Introduction. Research Basics. Survey Research. Experimentation and Observational Research. Secondary Data. The Basics of Sampling. Sampling Methods. Summary. Part II: PROBABILITY. 5. Probability: Review of Basic Concepts. Introduction. Probability: Terms and Approaches. Unions and Intersections of Events. Addition Rules for Probability. Multiplication Rules for Probability. Bayes' Theorem and the Revision of Probabilities. Counting: Permutations and Combinations. Summary. 6. Discrete Probability Distributions. Introduction. The Binomial Distribution. The Poisson Distribution. Simulating Observations from a Discrete Probability Distribution. Hypergeometric Distribution (Optional CD Topic). Summary. 7. Continuous Probability Distributions. Introduction. The Normal Distribution. The Standard Normal Distribution. The Normal Approximation to the Binomial Distribution. The Exponential Distribution. Simulating Observations from a Continuous Probability Distribution. Summary. Part III: SAMPLING DISTRIBUTIONS AND ESTIMATION. 8. Sampling Distributions. Introduction. A Preview of Sampling Distributions. The Sampling Distribution of the Mean. The Sampling Distribution of the Proportion. Sampling Distributions When the Population is Finite. Computer Simulation of Sampling Distributions. Summary. 9. Estimation From Sample Data. Introduction. Point Estimates. A Preview of Interval Estimates. Confidence Interval Estimates for the Mean: Sigma; Known. Confidence Interval Estimates for the Mean: Sigma; Unknown. Confidence Interval Estimates for the Population Proportion. Sample Size Determination. When the Population Is Finite. Summary. Part IV: HYPOTHESIS TESTING. 10. Hypothesis Tests Involving a Sample Mean or Proportion. Introduction. Hypothesis Testing: Basic Procedures. Testing a Mean, Population Standard Deviation Known. Confidence Intervals and Hypothesis Testing. Testing a Mean, Population Standard Deviation Unknown. Testing a Proportion. The Power of Hypothesis Test. Summary. 11. Hypothesis Tests Involving Two Sample Means or Proportions. Introduction. The Pooled Variances t-test for Comparing the Means of Two Independent Samples. The Unequal-Variances t-Test for Comparing the Means of Two Independent Samples. The z-Test for Comparing the Means of Two Independent Samples. Comparing Two Means when the Samples are Dependent. Comparing Two Sample Proportions. Comparing the Variances of Two Independent Samples. Summary. 12. Analysis of Variance Tests. Introduction. Analysis of Variance: Basic Concepts. One-Way Analysis of Variance. The Randomized Block Design. Two-Way Analysis of Variance. Summary. 13. Chi-Square Applications. Introduction. Basic Concepts in Chi-Square Testing. Tests for Goodness of Fit and Normality. Testing the Independence of Two Variables. Comparing Proportions from k Independent Samples. Estimation and Tests Regarding the Population Variance. Summary. 14. Nonparametric Methods. Introduction. Wilcoxon Signed Rank Test for One Sample. Wilcoxon Signed Rank Test for Comparing Paired Samples. Wilcoxon Rank Sum Test for Comparing Two Independent Samples. Friedman Test for the Randomized Block Design. Other Nonparametric Methods. Summary. Part V: REGRESSION, MODEL BUILDING, AND TIME SERIES. 15. Simple Linear Regressions and Correlation. Introduction. The Simple Linear Regression Model. Interval Estimation Using the Sample Regression Line. Correlation Analysis. Estimation and Tests Regarding the Sample Regression Line. Additional Topics in Regression and Correlation Analysis. Summary. 16. Multiple Regression and Correlation. Introduction. The Multiple Regression Model. Interval Estimation in Multiple Regression. Multiple Correlation Analysis. Significance Tests in Multiple Regression and Correlation. Overview of the Computer Analysis and Interpretation. Additional Topics in Multiple Regression and Correlation. Summary. 17. Model Building. Introduction. Polynomial Models with Two Quantitative Predictor Variables. Qualitative Variables. Data Transformations. Multicollinearity. Stepwise Regression. Selecting a Model. Summary. 18. Models for Time Series and Forecasting. Introduction. Time Series. Smoothing Techniques. Seasonal Indexes. Forecasting. Evaluating Alternative Models MAD and MSE. Auto-correlation, the Durbin-Watson Test, and Autoregressive Forecasting. Index Numbers. Summary. Part VI: SPECIAL TOPICS. 19. Decision Theory. Introduction. Structuring the Decision Situation. Non-Bayesian Decision Making. Bayesian Decision Making. The Opportunity Loss Approach. Incremental Analysis and Inventory Decisions. Summary. 20. Total Quality Management. Introduction. A Historical Perspective and Defect Detection. The Emergence of Total Quality Management. Practicing Total Quality Management. Some Statistical Tools for Total Quality Management. Statistical Process Control: The Concepts. Control Charts for Variables. Control Charts for Attributes. More on Computer-Assisted Statistical Process Control. Summary. 21. Ethics in Statistical Analysis and Reporting (Optional CD Chapter). Introduction. The Misuse of Statistical Techniques. The Computer: An Innocent Accomplice. The Significance of "Significance." Statistical Reports. Statistics in Society. Self-Defense for the Consumer of Statistical Information. Summary. Appendix A: Statistical Tables. Appendix B: Selected Answers. Index/Glossary.
"Weiers has done a good job of supporting the text with a plentiful number of business related problems. There also seems to be a good mix of problems that can be solved by hand and those that require a computer."
"I like the manner in which the material is introduced and explained through both the text and illustrations..."
"The book is well-written and easy to read. The graphics and illustrations are excellent. The learning objectives, opening chapter vignettes, statistics in action, and cases are excellent."
Highly praised for its clarity and great examples, Weiers' INTRODUCTION TO BUSINESS STATISTICS, 6E introduces fundamental statistical concepts in a conversational language that connects with today's students. Even those intimidated by statistics quickly discover success with the book's proven learning aids, outstanding illustrations, non-technical terminology, and hundreds of current examples drawn from real-life experiences familiar to students. A continuing case and contemporary applications combine with more than 100 new or revised exercises and problems that reflect the latest changes in business today with an accuracy you can trust. You can easily introduce today's leading statistical software and teach not only how to complete calculations by hand and using Excel, but also how to determine which method is best for a particular task. The book's student-oriented approach is supported with a wealth of resources, including the innovative new ThomsonNOWTM online course management and learning system that saves you time while helping students master the statistical skills most important for business success.
If you've ever felt intimidated or a little overwhelmed by business statistics, or if you simply want to master the power of these critical business skills, this book is for you. Weiers' INTRODUCTION TO BUSINESS STATISTICS, 6E speaks to you ? today's student ? introducing the fundamentals of business statistics in a conversational language and application setting that you can easily understand. Proven learning aids woven throughout the text, outstanding illustrations, and hundreds of examples build upon familiar, real-life experiences to help you develop a solid understanding of key statistical concepts. You'll discover how to use the statistical software most often chosen for business today. Also, you'll learn how to complete hand calculations and Excel applications ? and when it's best to use each. To further your understanding of today's statistics, a powerful online learning system ? CengageNOW ? helps you maximize your study time and efficiently complete homework with tutorials and interactive learning tools designed to focus specifically on the areas you individually need to master for business statistics success.
Measures of Central Tendency. Statistical
About the Author
Dr. Ron Weiers is an award-winning teacher and textbook author in the fields of business statistics and marketing research. He holds a passion for "making complicated things understandable," which is evident in the clear, conversational writing style found in his INTRODUCTION TO BUSINESS STATISTICS. Dr. Weiers is a recipient of the Indiana University of Pennsylvania Distinguished Faculty Award for Teaching. He is an adjunct professor at the H. John Heinz III School of Public Policy and Management, Carnegie Mellon University, and is Professor Emeritus at the Eberly College of Business and Information Technology, Indiana University of Pennsylvania.
Dr. Weiers has served as a marketing, technical and automotive consultant to organizations such as the Coleman Company, the U.S. Department of Energy, and the Society of Automotive Engineers. He has authored 8 automotive books on topics ranging from repair and maintenance to fuel efficiency and safety. Dr. Weiers has provided research and advisory services to the U.S. Department of Energy, National Highway Traffic Administration, and National Public Services Research Institute. He has developed Public Affairs Programs on Urban Transportation, Fuel Efficiency, Vehicle Safety, and Exhaust Emissions for the U.S. Headquarters of the Society of Automotive Engineers, and has authored an SAE Public Affairs Report on Automotive Noise Pollution.
Dr. Weiers earned his B.S. in Industrial Engineering at the University of Pittsburgh and his S.M. in Industrial Management from the Sloan School of Management at the Massachusetts Institute of Technology. He later received his Ph.D. in Marketing Research and Analysis from the University of Pittsburgh. Dr. Weiers is a member of several professional organizations, including the American Marketing Association, the American Statistical Association, the Decision Sciences Institute, and the Society of Automotive Engineers.
Table of Contents
"Weiers definitely is the best. The shorter chapter sections are the right length for our students. The author writes in clear and lucid prose, and is not "over their heads." This is the best book (out of five total) I have used in my fourteen years of teaching undergraduate statistics for business majors.""Overall, I like the quantity and quality of the exercises. I think this is the real strength of this textbook. Good coverage of basic statistics; chapters are well-written and easy to read/understand; great exercises.""I like the manner in which the material is introduced and explained through both the text and illustrations...""The book is well-written and easy to read. The graphics and illustrations are excellent. The learning objectives, opening chapter vignettes, statistics in action, and cases are excellent.""Weiers has done a good job of supporting the text with a plentiful number of business related problems. There also seems to be a good mix of problems that can be solved by hand and those that require a computer."