Statistics for Business and Economics + Supplement 13/e【經拆封不受退,不含Access Code】



2017 年13 版



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●REVISED APPROACH TO CALCULATING PERCENTILES. Chapter 3, Descriptive Statistics: Numerical Measures, now uses the approach recommended by the National Institute of Standards and Technology (NIST) and also used by a wide variety of software. In addition, the NIST-recommended approach for calculating percentiles is integrated throughout the textbook wherever percentiles are used (for example, when creating a box plot or when calculating quantiles or an interquartile range).
●MINDTAP® PROVIDES STUDENTS WITH TOOLS FOR BETTER TIME MANAGEMENT. Students can complete assignments whenever and wherever they are ready to learn with course material specially customized by you and streamlined in one proven, easy-to-use interface. MindTap® gives students a roadmap to master decision-making in business statistics. Its vast array of resources, tools, and apps -- including all new Excel Online activities powered by Microsoft, new Exploring Statistics interactive visualizations, problem-solving videos, animated examples and practice opportunities, Interpreting the Results assignments note taking, and flashcards -- ensures learners have everything they need to maximize course success.
●UPDATED APPENDICES INCLUDE THE LATEST SOFTWARE. All step-by-step instructions in the software appendices and all textbook figures featuring software output have been updated to reflect Excel 2013 and Minitab 17. This equips students with exposure to and hands-on experience with the current versions of two of the most commonly used software for statistical analysis in business.
●Unparalleled Software Options. Bundle options in support of popular statistics software packages are now available that include the latest versions of Minitab 17 and Minitab Express (Minitab Express is a new introductory statistics package that supports Mac computers), JMP, and SPSS. ‘Tip Sheets’ offer resources that include step-by-step instructions with screenshots that walk students through the software. The text DATAfiles are available in .csv format for easy import into these popular software packages. Contact your Cengage representative for ordering information!
●TWO ALL-NEW CASE PROBLEMS. A new probability modeling case has been added to Chapter 5, while a new simple linear regression case appears in Chapter 14. The 33 case problems in this book provide students the opportunity to put what they’ve learned into action by working on more complex problems, analyzing larger data sets, and preparing managerial reports based on the results of their analyses.v
●NEW EXAMPLES BASED ON REAL DATA. Bringing statistical concepts to life, more than 180 new examples and exercises reflect real data and referenced sources. Data from sources used by THE WALL STREET JOURNAL, USA TODAY, BARRON’S, and others draw from actual studies and applications to develop explanations and create exercises that demonstrate the many uses of statistics in business and economics. The 13th edition contains upwards of 350 examples and exercises based on real data.

●USE OF CUMULATIVE STANDARD NORMAL DISTRIBUTION TABLE PREPARES STUDENTS TO WORK WITH STATISTICAL SOFTWARE. To more effectively prepare students to readily use computer software in statistics, the text incorporates a normal probability table consistent with today’s statistical software. This cumulative normal probability table also makes it easier to compute p-values for hypothesis testing.
●TRUSTED TEAM OF DISTINGUISHED AUTHORS ENSURES THE MOST ACCURATE, PROVEN PRESENTATION. Prominent leaders and active consultants in business and statistics, authors David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, and James J. Cochran deliver an accurate, real-world presentation of statistical concepts you can trust with every edition.
●LEADING PROBLEM-SCENARIO APPROACH HELPS STUDENTS EASILY UNDERSTAND AND APPLY CONCEPTS. A hallmark strength of this text is its unique approach that ensures students fully comprehend statistical techniques within an applications setting. The statistical results provide insights into business decisions and detail how statistics are used within real-world practice to solve problems.
●SYSTEMATIC APPROACH EMPHASIZES PROVEN METHODS AND APPLICATIONS. Students first develop a computational foundation and thoroughly learn the use of techniques before moving to statistical application and interpretation of the value of techniques. Methods Exercises at the end of each section stress computation and use of formulas, while Application Exercises require students to apply what they know about statistics to real-world problems

Dr. David R. Anderson is a textbook author and Professor Emeritus of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. He has served as head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration. He was also coordinator of the College’s first Executive Program. In addition to introductory statistics for business students, Dr. Anderson has taught graduate-level courses in regression analysis, multivariate analysis, and management science. He also has taught statistical courses at the Department of Labor in Washington, D.C. Professor Anderson has received numerous honors for excellence in teaching and service to student organizations. He is the coauthor of ten textbooks related to decision sciences and actively consults with businesses in the areas of sampling and statistical methods. Born in Grand Forks, North Dakota, he earned his BS, MS, and PhD degrees from Purdue University.

Dr. Dennis J. Sweeney is a leading textbook author, Professor Emeritus of Quantitative Analysis, and founder of the Center for Productivity Improvement at the University of Cincinnati. He also served five years as head of the Department of Quantitative Analysis and four years as Associate Dean of the College of Business Administration. In addition, Dr. Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Dr. Sweeney has published more than 30 articles in the area of management science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger, and Cincinnati Gas & Electric have funded his research, which has been published in Management Science, Operations Research, Mathematical Programming, Decision Sciences, and other respected journals. Dr. Sweeney is the co-author of ten textbooks in the areas of statistics, management science, linear programming, and production and operations management. Born in Des Moines, Iowa, he earned a B.S. degree from Drake University, graduating summa cum laude. He received his M.B.A. and D.B.A. degrees from Indiana University, where he was an NDEA Fellow.

Dr. Thomas A. Williams is a well respected textbook author and Professor Emeritus of Management Science in the College of Business at Rochester Institute of Technology, where he was the first chairman of the Decision Sciences Department. He taught courses in management science and statistics, as well as graduate courses in regression and decision analysis. Before joining the College of Business at RIT, Dr. Williams served for seven years as a faculty member in the College of Business Administration at the University of Cincinnati, where he developed the undergraduate program in Information Systems and served as its coordinator. The co-author of 11 leading textbooks in the areas of management science, statistics, production and operations management, and mathematics, Dr. Williams has been a consultant for numerous Fortune 500 companies and has worked on projects ranging from the use of data analysis to the development of large-scale regression models. He earned his B.S. degree at Clarkson University and completed his graduate work at Rensselaer Polytechnic Institute, where he received his M.S. and Ph.D. degrees.

Jeffrey D. Camm is the Inmar Presidential Chair and Associate Dean of Analytics in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a B.S. from Xavier University in Ohio, and a Ph.D. from Clemson University. Prior to joining the faculty at Wake Forest, he served on the faculty of the University of Cincinnati. He has also been a visiting scholar at Stanford University and a visiting professor of business administration at the Tuck School of Business at Dartmouth College. Dr. Camm has published more than 30 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in Science, Management Science, Operations Research, Interfaces, and other professional journals. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati and he was the 2006 recipient of the INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing what he preaches, he has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010 he served as editor-in-chief of Interfaces and has also served on the editorial board of INFORMS Transactions on Education.

James J. Cochran is Professor of Applied Statistics and the Rogers-Spivey Faculty Fellow at the University of Alabama. Born in Dayton, Ohio, he earned
his B.S., M.S., and M.B.A. degrees from Wright State University and a Ph.D. from the
University of Cincinnati. He has been at the University of Alabama since 2014 and has
been a visiting scholar at Stanford University, Universidad de Talca, the University of
South Africa and Pole Universitaire Leonard de Vinci.

1. Data and Statistics.
2. Descriptive Statistics: Tabular and Graphical Displays.
3. Descriptive Statistics: Numerical Measures.
4. Introduction to Probability.
5. Discrete Probability Distributions.
6. Continuous Probability Distributions.
7. Sampling and Sampling Distributions.
8. Interval Estimation.
9. Hypothesis Tests.
10. Inference about Means and Proportions with Two Populations.
11. Inferences about Population Variances.
12. Comparing Multiple Proportions, Test of Independence and Goodness of Fit.
13. Experimental Design and Analysis of Variance.
14. Simple Linear Regression.
15. Multiple Regression.
16. Regression Analysis: Model Building.
17. Time Series Analysis and Forecasting.
18. Nonparametric Methods.
19. Statistical Methods for Quality Control.
20. Index Numbers.
21. Decision Analysis (online).
22. Sample Survey (online).
Appendix A. References and Bibliography.
Appendix B. Tables.
Appendix C. Summation Notation.
Appendix D. Self-Test Solutions and Answers to Even–Numbered Exercises.
Appendix E. Microsoft Excel 2013 and Tools for Statistical Analysis.
Appendix F. Computing p-Values Using Minitab and Excel.