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MindTap Business Statistics, 2 terms (12 months) Instant Access for Anderson/Sweeney/Williams/Camm/Cochran's Statistics for Business & Economics, Revised, 13th Edition

David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran

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Starting At $99.95 See pricing and ISBN options
MindTap Business Statistics, 2 terms (12 months) Instant Access for Anderson/Sweeney/Williams/Camm/Cochran's Statistics for Business & Economics, Revised 13th Edition by David R. Anderson/Dennis J. Sweeney/Thomas A. Williams/Jeffrey D. Camm/James J. Cochran

Overview

Clearly demonstrate how statistical information enables strong decisions in today\u2019s business world with MindTap Business Statistics with XLSTAT for Anderson/Sweeney/Williams/Camm/Cochran's Statistics for Business & Economics, Revised, 13th Edition. Sound methodology combines with a proven problem-scenario approach, and meaningful applications for the most powerful approach to teaching business statistics available. Prestigious authors bring more than 25 years of unmatched experience to this thoroughly updated text. More than 350 real business examples, cases, and memorable exercises present the latest statistical data and business information with unwavering accuracy. You select the topics to give you the most relevant text for your course, including coverage of popular commercial statistical software, such as Minitab 17 and Excel 2016. Excel add-in XLSTAT is also available. Optional chapter appendices, coordinating data sets, and online courseware, MindTap, creates a customizable, efficient solution.

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 10 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 of Analytics and Senior Associate Dean for Faculty 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, Dr. Camm 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 Science, Management Science, Operations Research, The INFORMS Journal on Applied Analytics and other professional journals. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati and he was the recipient of the 2006 INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing what he preaches, he has served as a consultant to numerous companies and government agencies. Dr. Camm served as editor-in-chief of INFORMS Journal on Applied Analytics and is an INFORMS fellow.

James J. Cochran

James J. Cochran is Professor of Applied Statistics, the Mike and Cathy Mouron Research Chair and Associate Dean for Faculty and Research 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 his Ph.D. from the University of Cincinnati. Dr. Cochran has served 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. Dr. Cochran has published more than 50 papers in the development and application of operations research and statistical methods. He has published his research in 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. He was the 2008 recipient of the INFORMS Prize for the Teaching of Operations Research Practice and the 2010 recipient of the Mu Sigma Rho Statistical Education Award. He received the Founders Award in 2014 and the Karl E. Peace Award in 2015 from the American Statistical Association. In 2017 he received the American Statistical Association’s Waller Distinguished Teaching Career Award and in 2018 he received the INFORMS President’s Award. Dr. Cochran is an elected member of the International Statistics Institute, a fellow of the American Statistical Association and a fellow of INFORMS. A strong advocate for effective statistics and operations research education as a means of improving the quality of applications to real problems, Dr. Cochran has organized and chaired teaching workshops throughout the world.
  • 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.
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.
MindTap
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  • ISBN-10: 1337094188
  • ISBN-13: 9781337094184
  • RETAIL $99.95