Course in Business Statistics, A

by Groebner, David F.; Shannon, Patrick W.; Fry, Phillip C; Smith, Kent D.

• ISBN13: 9780130936578
• ISBN10: 013093657X
• Edition: 3rd
• Format: Hardcover
• Copyright: 2006-01-01
• Publisher: Pearson College Div

Summary

This book presents core topics in descriptive and inferential statistics with a rich assortment of business examples and real data, and an emphasis on decision-making. It contains a narrative writing style--and the captivating examples and applications, and rich data sets are woven right into the narrative. The examples are interesting, realistic and drawn from all areas of business and life. There is significant emphasis on using statistical software as a tool, with most examples presented in a spreadsheet environment using Excel and Minitab. Every topic is introduced in the context of a real business application complete with real data, from small and large data sets.

Table of Contents

The Where, Why, and How of Data Collection	1	(36)
Graphs, Charts, and Tables--Describing Your Data	37	(44)
Describing Data Using Numerical Measures	81	(42)
Using Probability and Discrete Probability Distributions	123	(63)
Continuous Probability Distributions	186	(31)
Introduction to Sampling Distributions	217	(40)
Estimating Population Values	257	(34)
Introduction to Hypothesis Testing	291	(42)
Hypothesis Testing and Estimation for Two Population Parameters	333	(45)
Analysis of Variance	378	(36)
Introduction to Linear Regression and Correlation Analysis	414	(52)
Multiple Regression Analysis and Model Building	466	(43)
Analyzing and Forecasting Time-Series Data	509
CD-ROM CHAPTERS
Goodness-of-Fit Tests and Contingency Analysis	1	(1)
Introduction to Nonparametric Statistics	1	(1)
Introduction to Quality and Statistical Process Control	1	(1)
Introduction to Decision Analysis	1	(587)
Appendix A Random Numbers Table	588	(1)
Appendix B Binomial Distribution Table--Individual Probabilities	589	(9)
Appendix B1 Binomial Distribution Table--Cumulative Probabilities	598	(20)
Appendix C Poisson Probability Distribution Table	618	(5)
Appendix D Standard Normal Distribution Table	623	(1)
Appendix E Exponential Distribution Table	624	(1)
Appendix F Values of t for Selected Probabilities	625	(3)
Appendix G Values of X2 for Selected Probabilities	628	(1)
Appendix H F-Distribution Table	629	(4)
Appendix I Critical Values of Hartley's Fmax Test	633	(1)
Appendix J Distribution of the Studentized Range	634

Excerpts

New business school graduates face an increasingly competitive job market. While the U.S. economy continues to perform well, corporate downsizing along with competitive pressures to trim costs have affected the demand for new graduates in most business majors. In order to stand out in today's competitive job market, graduates need to bring to an organization special skills and abilities that give them the potential to hit the ground running and contribute immediately. One area where a student can have an immediate competitive advantage over both new graduates and existing employees is in the application of statistical analysis skills to business problems. While most colleges of business require their undergraduates and MBA-level students to have completed either one or two business statistics courses, too many students complete their academic programs without having mastered the statistical skills necessary to meet the needs of business. One reason for this may be that their statistics courses did not adequately prepare them in applying statistical tools and concepts to real-world decision-making problems. Our intent in writing a third edition ofA Course in Business Statisticsis to build on the strengths of the previous two additions (readability, decision-making focus, content coverage, pedagogical aids, etc.) and to take the text to a new level of performance. In doing so, we have made substantive changes throughout the text so that students can more fully and completely appreciate the value of business statistics to both their academic and professional careers. Dr. Phil Fry of Boise State University and Dr. Kent Smith of Cal Polytechnic State University of San Luis Obispo have joined Professors David Groebner and Patrick Shannon as co-authors. All the authors share a passion for the subject, as well as a devotion to teaching, and have significant experience in applying the statistical tools in business and industry settings. Below is a description of the major improvements we have made to this edition. STUDENTS USING REAL BUSINESS APPII(ATIONS The third edition ofA Course in Business Statisticsprovides real-world applications as a motivation for learning business statistics. While previous editions have focused on decision making and business applications, the new edition is more applied than ever before. Not only do the chapters focus on real companies and actual applications, increased effort has been placed on providing the student with an understanding of the role business statistics plays in decision making. This text is designed to help the instructor create a climate where students are motivated to learn and apply statistical techniques. We believe that students will relate well to the writing style used throughout the text. The writing style and subject presentation are intended to facilitate student interest and involvement in the material. Statistical concepts and techniques are introduced through realistic business situations, and we have made every effort to communicate ideas using a nontechnical writing style. This is a business statistics text that students will actually read and use to increase their understanding of business statistics. INCREASED COMPUTER EMPHASIS To enhance the students' appreciation for business statistics, we emphasize computer-based analysis, rather than manual computations. Toward this end, Microsoft's Excel (Office 2000 version) is featured extensively throughout the textbook. Minitab is also used as a supplement to Excel at various places throughout the text. Chapter examples, exercises, and case studies are based on real industry data or data motivated by real-world examples. In this way, students gain a greater understanding of what statistical tools to use, when and how to apply them, and how to interpret the results of their analyses to decision making. Unlike some computer-based textbooks that provided only end-