Statistics for Business & Economics, Revised (with XLSTAT Education Edition Printed Access Card),
13th Edition

Preface.
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 (On Website).
22. Sample Survey (On Website).
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 2016 and Tools for Statistical Analysis.
Appendix F: Computing p-Values Using Minitab and Excel.
Index.

• David R. Anderson

  David R. Anderson is a leading author and professor emeritus of quantitative analysis in the College of Business Administration at the University of Cincinnati. Dr. Anderson 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 taught graduate-level courses in regression analysis, multivariate analysis and management science. He also taught statistical courses at the Department of Labor in Washington, D.C. Dr. Anderson has received numerous honors for excellence in teaching and service to student organizations. He is the co-author of ten well-respected textbooks related to decision sciences, and he actively consults with businesses in the areas of sampling and statistical methods. Born in Grand Forks, North Dakota, Dr. Anderson earned his B.S., M.S. and Ph.D. degrees from Purdue University.

• Dennis J. Sweeney

  Dennis J. Sweeney is professor emeritus of quantitative analysis and founder of the Center for Productivity Improvement at the University of Cincinnati. Born in Des Moines, Iowa, he earned a B.S.B.A. degree from Drake University and his M.B.A. and D.B.A. degrees from Indiana University, where he was an NDEA fellow. Dr. Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. He also served as head of the Department of Quantitative Analysis and served four years as associate dean of the College of Business Administration at the University of Cincinnati. Dr. Sweeney has published more than 30 articles and monographs 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 journals such as Management Science, Operations Research, Mathematical Programming and Decision Sciences. Dr. Sweeney has co-authored ten textbooks in the areas of statistics, management science, linear programming and production and operations management.

• Thomas A. Williams

  N/A

• Jeffrey D. Camm

  Jeffrey D. Camm is the Inmar Presidential Chair and senior associate dean of business analytics programs in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a B.S. from Xavier University (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 45 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in many professional journals, including Science, Management Science, Operations Research and the INFORMS Journal on Applied Analytics. 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, Dr. Camm has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010 he served as editor-in-chief of the INFORMS Journal on Applied Analytics (formerly Interfaces). In 2016 Dr. Camm received the George E. Kimball Medal for service to the operations research profession, and in 2017 he was named an INFORMS fellow.

• James J. Cochran

  James J. Cochran is associate dean for research, a 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. from Wright State University and his Ph.D. from the University of Cincinnati. He has been at The University of Alabama since 2014 and has served as a visiting scholar at Stanford University, Universidad de Talca, the University of South Africa and Pole Universitaire Leonard de Vinci. Dr. Cochran has published more than 50 papers in the development and application of operations research and statistical methods. He has published in numerous journals, including Management Science, The American Statistician, Communications in Statistics-Theory and Methods, Annals of Operations Research, European Journal of Operational Research, Journal of Combinatorial Optimization, INFORMS Journal on Applied Analytics, BMJ Global Health and Statistics and Probability Letters. Dr. Cochran received the 2008 INFORMS prize for the Teaching of Operations Research Practice, the 2010 Mu Sigma Rho Statistical Education Award and the 2016 Waller Distinguished Teaching Career Award from the American Statistical Association. Dr. Cochran was elected to the International Statistics Institute in 2005 and was named a fellow of the American Statistical Association in 2011 and a fellow of INFORMS in 2017. He also received the Founders Award in 2014 and the Karl E. Peace Award in 2015 from the American Statistical Association. In addition, he received the INFORMS President's Award in 2019. A strong advocate for effective operations research and statistics education as a means of improving the quality of applications to real problems, Dr. Cochran has chaired teaching effectiveness workshops around the globe. He has also served as an operations research or statistics consultant to numerous companies and not-for-profit organizations.

• TRUSTED TEAM OF EXPERT AUTHORS ENSURES THE MOST ACCURATE, PROVEN PRESENTATION. As prominent, respected leaders and active consultants in business and statistics today, authors David R. Anderson, Dennis J. Sweeney, and Thomas A. Williams, Jeffrey D. Camm, and James J. Cochran provide an accurate timely presentation of statistical concepts you and your students can trust with every edition.

• LEADING PROBLEM-SCENARIO APPROACH HELPS STUDENT UNDERSTAND AND APPLY CONCEPTS. A hallmark strength of this text, this unique problem-scenario approach guides students in understanding statistical techniques within an applications setting. The statistical results provide insights into business decisions and detail how professionals regularly use statistics in business to solve problems.

• SYSTEMATIC APPROACH EMPHASIZES PROVEN METHODS AND APPLICATIONS. Students first develop a computational foundation and learn to use techniques before moving to statistical application and interpretation of the value of techniques. Methods Exercises at the end of each section stress computation and the use of formulas, while Application Exercises require students to use what they know about statistics to address real-world problems.

• CENGAGENOW™ ONLINE COURSE MANAGEMENT SYSTEM PROVIDES STUDENT RESULTS NOW. This robust, online course management system gives you more control in less time and delivers better student outcomes. Teaching and learning resources are organized around lectures and enable you to create assignments and quizzes and track student progress and performance easily. Flexible assignments, automatic grading and a gradebook option provide more control while saving you valuable time. A Personalized Study diagnostic tool empowers students to master concepts, prepare for exams, and become more involved in class.

• USE OF CUMULATIVE STANDARD NORMAL DISTRIBUTION TABLE PREPARES STUDENTS TO WORK WITH STATISTICAL SOFTWARE. To more effectively prepare today's students to use computer software in statistics, this book incorporates a normal probability table that is consistent with today's most popular statistical software. This cumulative normal probability table also makes it easier to compute p-values for hypothesis testing.

• COVERAGE HIGHLIGHTS DATA MINING, BIG DATA AND ANALYTICS. A proven section on analytics describes what analytics is, the types of analytics used in business and how this relates to statistics. An expanded section on data mining includes a discussion of big data and how businesses today are using data mining to establish competitive advantages.

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