Working With Sample Data: Exploration and Inference

Chaffe-Stengel Priscilla M Stengel Donald N. Chaffe-Stengel Priscilla

ISBN 10: 1606492136 / ISBN 13: 9781606492130

Published by Business Expert Press, 2011

About this Item

pp. x + 151 Illus.

Seller Inventory # 5884916

Bibliographic Details

• Title: Working With Sample Data: Exploration and Inference
• Publisher: Business Expert Press
• Publication Date: 2011
• Language: English
• ISBN 10: 1606492136
• ISBN 13: 9781606492130
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Managers and analysts routinely collect and examine key performance measures to better understand their operations and make good decisions. Being able to render the complexity of operations data into a coherent account of significant events requires an un

About the Authors

Priscilla Chaffe-Stengel is a professor of Information Systems and Decision Sciences at California State University, Fresno. She received a PhD in design and evaluation of educational programs, an educational specialist degree in program evaluation from Stanford University, and an MA in mathematics from California State University, Fresno. Dr. Chaffe-Stengel has taught statistical analysis, quantitative analysis, and sampling at the university level; coordinates the quantitative and statistical analysis courses in the Craig School of Business; and teaches in both the MBA program and executive MBA program.

Donald N. Stengel is a professor and chair of the Department of Information Systems and Decision Sciences at California State University, Fresno. Previously he served as the director of the MBA program at California State University, Fresno. He received a PhD in engineering-economic systems from Stanford University. Prior to joining the faculty at California State University, Fresno, Dr. Stengel worked for 8 years as a management consultant, developing planning models for agriculture and energy. He teaches in both the MBA program and executive MBA program and is a member of the National Association for Business Economics, the Institute for Operations Research and Management Science, and the American Statistical Association.