David F. Groebner, Patrick W. Shannon, Phillip C. Fry

Business Statistics: A Decision Making Approach, Global Edition (eBook, PDF)

• Format: PDF

Produktbeschreibung

For 2-semester courses in Introductory Business Statistics.

Applies statistical analysis to real-world decision making

Business Statistics: A Decision-Making Approach, 11th Edition, is an introductory text for students who do not necessarily have an extensive mathematics background but who need to understand how statistical tools and techniques are applied in business decision making. Concepts and techniques presented in a systematic and ordered way make this text accessible to all students. The authors draw from their years of experience as consultants, educators, and writers to show the relevance of statistical techniques in realistic situations through engaging examples.

This text seamlessly integrates computer applications, such as Microsoft Excel and XLSTAT, with textual examples and figures, always focusing on interpreting the output. The goal is for students to be able to know which tools to use, how to apply the tools, and how to analyze results for making decisions.

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Produktdetails

• Verlag: Pearson HigherEducation
• Altersempfehlung: ab 18 Jahre
• Erscheinungstermin: 9. August 2023
• Englisch
• ISBN-13: 9781292446257
• Artikelnr.: 68596096

Autorenporträt

About our authors

David F. Groebner is Professor Emeritus of Production Management in the College of Business and Economics at Boise State University. He has bachelor's and master's degrees in engineering and a Ph.D. in business administration. After working as an engineer, he has taught statistics and related subjects for 27 years. In addition to writing textbooks and academic papers, Groebner has worked extensively with both small and large organizations, including Hewlett-Packard, Boise Cascade, Albertson's, and Ore-Ida. He has worked with numerous government agencies, including Boise City and the U.S. Air Force.

Patrick W. Shannon, Ph.D. is Dean and Professor of Supply Chain Operations Management in the College of Business and Economics at Boise State University. In addition to his administrative responsibilities, he has taught graduate and undergraduate courses in business statistics, quality management, and production and operations management. In addition, Dr. Shannon has lectured and consulted in the statistical analysis and quality management areas for more than 20 years. Among his consulting clients are Boise Cascade Corporation, Hewlett-Packard, PowerBar, Inc., Potlatch Corporation, Woodgrain Millwork, Inc., J.R. Simplot Company, Zilog Corporation, and numerous other public- and private-sector organizations. Shannon has co-authored several university-level textbooks and has published numerous articles in such journals as Business Horizons, Interfaces, Journal of Simulation, Journal of Production and Inventory Control, Quality Progress, and Journal of Marketing Research. He obtained B.S. and M.S. degrees from the University of Montana and a Ph.D. in statistics and quantitative methods from the University of Oregon.

Phillip C. Fry is a professor in the College of Business and Economics at Boise State University, where he has taught since 1988. Phil received his B.A. and M.B.A. degrees from the University of Arkansas and his M.S. and Ph.D. degrees from Louisiana State University. His teaching and research interests are in the areas of business statistics, supply chain management, and quantitative business modeling. In addition to his academic responsibilities, Fry has consulted with and provided training to small and large organizations, including Boise Cascade Corporation, Hewlett-Packard Corporation, the J.R. Simplot Company, United Water of Idaho, Woodgrain Millwork, Inc., Boise City, and Intermountain Gas Company.

Inhaltsangabe

1. The Where, Why, and How of Data
2. Graphs, Charts, and Tables: Describing Your Data
3. Describing Data Using Numerical Measures
1 - 3 SPECIAL REVIEW SECTION
1. Introduction to Probability
2. Discrete Probability Distributions
3. Introduction to Continuous Probability Distributions
4. Introduction to Sampling Distributions
5. Estimating Single Population Parameters
6. Introduction to Hypothesis Testing
7. Estimation and Hypothesis Testing for Two Population Parameters
8. Hypothesis Tests and Estimation for Population Variances
9. Analysis of Variance
8 - 12 SPECIAL REVIEW SECTION
10. Goodness-of-Fit Tests and Contingency Analysis
11. Introduction to Linear Regression and Correlation Analysis
12. Multiple Regression Analysis and Model Building
13. Analyzing and Forecasting Time-Series Data
14. Introduction to Nonparametric Statistics
15. Introducing Business Analytics
16. Introduction to Decision Analysis (Online)
17. Introduction to Quality and Statistical Process Control (Online)
APPENDICES A to P