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Essentials of Modern Business Statistics with Microsoft® Excel® 5th Edition

David R. Anderson, Dennis J. Sweeney, Thomas A. Williams

  • Published
  • Previous Editions 2009, 2007, 2004
  • 784 Pages


ESSENTIALS OF MODERN BUSINESS STATISTICS, 5TH EDITION provides an introduction to business statistics that blends a conceptual understanding of statistics with the real-world application of statistical methodology. Microsoft Excel® 2010 is integrated throughout the text, showing step-by-step instructions and screen captures to enhance student learning. The fifth edition contains the same student learning features that have made ASW products best-sellers for years, including the problem-scenario approach and real-world examples that introduce statistical techniques. A student companion site comes includes: Case Files, Example Files, Problem Files, Tutorials, Solvertable, Palisade DecisionTools (StatTools), Excel Tutorial.

David R. Anderson, University of Cincinnati

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.

Dennis J. Sweeney, University of Cincinnati

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.

Thomas A. Williams, Rochester Institute of Technology

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.
  • NEW! Integration of Microsoft Excel® 2010. Step-by-step instructions and screen captures show how to use Excel 2010 to implement statistical procedures.
  • NEW! Revised Chapter 2. Excel coverage has been condensed by moving the discussion of how to use Excel's Pivot Chart Report to chapter appendixes. Appendix 2.1 shows how to use Excel's Pivot Chart Report to summarize categorical data and Appendix 2.2 shows how to use Excel's Pivot Chart report to summarize quantitative data.
  • NEW! Revised Sampling Material. The Chapter 7 introduction has been revised and now includes the concept of a sampled population and a frame. The distinction between sampling from a finite population and an infinite population has been clarified, with sampling from an ongoing process used to illustrate the selection of a random sample from an infinite population. A practical advice section stresses the importance of obtaining close correspondence between the sampled population and the target population.
  • NEW! Revised Introduction to Hypothesis Testing. Section 9.1, Developing Null and Alternative Hypotheses, has been revised. A better set of guidelines has been developed for identifying the null and alternative hypotheses. The context of the situation and the purpose for taking the sample are key. In situations in which the focus is on finding evidence to support a research finding, the research hypothesis is the alternative hypothesis. In situations where the focus is on challenging an assumption, the assumption is the null hypothesis.
  • NEW! Section 13.8 – Modeling Curvilinear Relationships. This new section shows how curvilinear relationships can be handled easily using a multiple regression model. We illustrate the use of both Excel's Chart tools and Excel's Regression tool to fit a quadratic model.
  • NEW! Chapter 14 – Time Series Analysis and Forecasting. Section 14.1 discusses time series patterns and Section 14.2 introduces methods for measuring forecasting accuracy. Section 14.3 discusses moving averages and exponential smoothing. Section 14.4 introduces methods appropriate for a time series that exhibits a trend. Here we illustrate how regression analysis can be used for trend projection to model nonlinear relationships involving a quadratic trend. Section 14.5 then shows how dummy variables can be used to model seasonality in a forecasting equation. Section 14.6 discusses classical time series decomposition including the concept of deseasonalizing a time series.
  • INTEGRATION OF EXCEL. Immediately following every statistical procedure is a sub-section that discusses how to use Excel to perform that procedure. This style enables the use of Excel to be integrated throughout the text, but still keeps the primary emphasis on the statistical methodology being discussed. Each sub-section uses a consistent framework for applying Excel to help users focus on the statistical methodology without getting bogged down in the details of using Excel.
  • OUTSTANDING EXERCISES. The end-of-section exercises are split into two parts: Methods and Applications. The Methods exercises require students to use formulas and make appropriate computations. The Applications exercises require students to use the chapter material in real-world situations. Many of the Applications exercises are based on recent data obtained from referenced sources. Combining these two methods enables students to focus on the computational "nuts and bolts" and then move on to the subtleties of statistical application and interpretation. Certain exercises are identified as self-test exercises and have completely worked-out-solutions provided in Appendix D.
  • MARGIN ANNOTATIONS AND NOTES AND COMMENTS. Margin annotations that highlight key points and provide additional insights for the students are a key feature of this text. These annotations are designed to provide emphasis and enhance understanding of the terms and concepts being presented. At the end of many sections, we provide Notes and Comments designed to give the student additional insights about the statistical methodology and its application. Notes and Comments include warnings about or limitations of the methodology, recommendations for application, brief descriptions of additional technical considerations, and other matters.
  • Included with the purchase of the new book is the Student Complimentary Site that gives access to WEBfiles and Palisade Decision Tools (Stat Tools).
  • PROBLEM-SCENARIO APPROACH. Using this approach, the discussion and development of each technique is presented in an applications setting, with the statistical results providing insights to decisions and solutions to problems. The problem scenarios enable students to see how statistics can be applied in business and economics and increase student interest and motivation for learning statistics.
  • STUDENT READABILITY. For more than 30 years, student surveys and instructor feedback have shown that readability is a hallmark of ASW textbooks.
1. Data and Statistics.
2. Descriptive Statistics: Tabular and Graphical Presentations.
3. Descriptive Statistics: Numerical Measures.
4. Introduction to Probability.
5. Discrete Probability Distribution.
6. Continuous Probability Distributions.
7. Sampling and Sampling Distributions.
8. Interval Estimation.
9. Hypothesis Testing.
10. Comparisons Involving Means, Experimental Design, and Analysis of Variance.
11. Comparisons Involving Proportions and a Test of Independence.
12. Simple Linear Regression.
13. Multiple Regression.
14. Time Series Analysis and Forecasting.
15. Statistical Methods for Quality Control.
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 2010 and Tools for Statistical Analysis.

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  • ISBN-10: 1133829112
  • ISBN-13: 9781133829119
  • STARTING AT $24.49

  • STARTING AT $51.49

  • ISBN-10: 0840062389
  • ISBN-13: 9780840062383
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