
Business Statistics, Global Edition
Pearson Education Limited (Publisher)
10th Edition
Published on 12. January 2018
Book
Paperback/Softback
928 pages
978-1-292-22038-3 (ISBN)
Shipment within 10-20 days
Description
Business Statistics: A Decision Making Approach provides students with an introduction to business statistics and to the analysis skills and techniques needed to make successful real-world business decisions.
Written for students of all mathematical skill levels, the authors present concepts in a systematic and ordered way, drawing from their own experience as educators and consultants. Rooted in the theme that data are the starting point, Business Statistics champions the need to use and understand different types of data and data sources to be effective decision makers.
This new edition integrates Microsoft Excel throughout as a way to work with statistical concepts and give students a resource that can be used in both their academic and professional careers.
Written for students of all mathematical skill levels, the authors present concepts in a systematic and ordered way, drawing from their own experience as educators and consultants. Rooted in the theme that data are the starting point, Business Statistics champions the need to use and understand different types of data and data sources to be effective decision makers.
This new edition integrates Microsoft Excel throughout as a way to work with statistical concepts and give students a resource that can be used in both their academic and professional careers.
More details
Edition
10th edition
Language
English
Place of publication
Harlow
United Kingdom
Target group
Professional and scholarly
Dimensions
Height: 274 mm
Width: 214 mm
Thickness: 30 mm
Weight
1560 gr
ISBN-13
978-1-292-22038-3 (9781292220383)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

David Groebner | David F. Groebner | Patrick W. Shannon
Business Statistics: A Decision Making Approach, Global Edition
Book
08/2023
11th Edition
Pearson Education Limited
€90.49
Shipment within 10-20 days
Additional editions

David F. Groebner | Patrick W. Shannon | Phillip C. Fry
Business Statistics, Global Edition
Global Edition
E-Book
09/2017
1st Edition
Pearson Education Limited
€63.29
Available for download
Previous edition
David F. Groebner | Patrick W. Shannon | Phillip C Fry
Business Statistics: Pearson New International Edition
Book
07/2013
9th Edition
Pearson Education Limited
€81.70
Article exhausted; check for reprint
Persons
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 organisations, 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 organisations. 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 organisations, 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.
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 organisations. 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 organisations, 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.
Content
The Where, Why, and How of Data Collection
Graphs, Charts, and Tables-Describing Your Data
Describing Data Using Numerical Measures
Introduction to Probability
Discrete Probability Distributions
Introduction to Continuous Probability Distributions
Introduction to Sampling Distributions
Estimating Single Population Parameters
Introduction to Hypothesis Testing
Estimation and Hypothesis Testing for Two Population Parameters
Hypothesis Tests and Estimation for Population Variances
Analysis of Variance
Goodness-of-Fit Tests and Contingency Analysis
Introduction to Linear Regression and Correlation Analysis
Multiple Regression Analysis and Model Building
Analyzing and Forecasting Time-Series Data
Introduction to Nonparametric Statistics
Introducing Business Analytics
Graphs, Charts, and Tables-Describing Your Data
Describing Data Using Numerical Measures
Introduction to Probability
Discrete Probability Distributions
Introduction to Continuous Probability Distributions
Introduction to Sampling Distributions
Estimating Single Population Parameters
Introduction to Hypothesis Testing
Estimation and Hypothesis Testing for Two Population Parameters
Hypothesis Tests and Estimation for Population Variances
Analysis of Variance
Goodness-of-Fit Tests and Contingency Analysis
Introduction to Linear Regression and Correlation Analysis
Multiple Regression Analysis and Model Building
Analyzing and Forecasting Time-Series Data
Introduction to Nonparametric Statistics
Introducing Business Analytics