Statistics for business : data analysis and modeling

書誌事項

Statistics for business : data analysis and modeling

Jonathan D. Cryer, Robert B. Miller

(Duxbury series in business statistics and decision sciences)

Duxbury Press, c1994

2nd ed

  • :alk. paper

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注記

System requirements for computer data disk (DOS Minitab worksheets and macros): IBM PC; DOS; Minitab

Includes bibliographical references (p. 832-836) and index

内容説明・目次

内容説明

This text employs the latest ideas in teaching business statistics and follows the philosophy espoused at the conference "Making Statistics More Effective in Schools of Business" (MSMESB). It emphasizes modern statistical methods and data analysis with a decreased emphasis on classical hypothesis testing and probability. It presents a problem-solving approach to the analysis of real data sets and procedures for data collection, design, and interpretation. It covers statistics in the context of the scientific method for problem recognition, problem formulation, and problem solving. Concrete examples of statistical techniques and computer use give students a practical framework of business statistics in practice.

目次

PART ONE: DATA COLLECTION 1. Data Analysis and Model Building: An Introduction 2. Plotting Process Data 3. Plotting Distributions 4. Summarizing Continuous Data 5. Describing Categorical Variables 6. Relating Continuous Variables PART TWO: ELEMENTS OF MODELING 7. Straight Line Models 8. Multiple Regression Models 9. Normal Distributions 10. Control Charts for Continuous Variables 11. Binomial distributions 12. Control Charts for Binary Data PART THREE: RANDOMIZED DATA COLLECTION AND INFERENCE 13. Data Collection Tools 14. Introduction to Surveys 15. Survey Designs 16. Reading the Results of a Survey 17. Significance Tests and Confidence Intervals 18. Completely Randomized and Randomized Block Designs and the Analysis of Variance 19. Factorial and Fractional Factorial Designs PART FOUR: MODELING AND INFERENCE 20. Inference and Regression Models 21. Regression Diagnostics and Transformations 22. Regression Model Selection 23. Time Series Models 24. Seasonal Time Series Models PART FIVE: STATISTICS AND ORGANIZATIONS 25. A Perspective on Statistics in Organization Appendices / References / Glossary / Answers to Selected Exercises / Data Set Index / Index

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