Title Details

Johannes Ledolter is a Professor at the University of Iowa in the Department of Statistics and Actuarial Science and the Department of Management Sciences, and a Professor at the Wirtschaftsuniversität Vienna, Austria. He received a Ph.D. in Statistics from the University of Wisconsin-Madison in 1975. Professor Ledolter held visiting positions at the University of Wisconsin, Princeton University, and Yale University. His area of research centers around time series analysis and forecasting, statistical methods for quality improvement, and applications of statistics in business and engineering. He has coauthored the books Statistical Methods for Forecasting, published by Wiley in 1983, and Applied Statistics for Engineers and Physical Scientists, published by Macmillan (Prentice Hall) in 1992.He and Dr. Burrill are coauthors of the book Achieving Quality Through Continual Improvement, published by Wiley in 1999. Professor Ledolter is a Fellow of the American Statistical Association, and an Elected Member of the International Statistical Institute.

Dr. Claude W. Burrill is a consultant on quality and project management. He is an Adjunct Professor in the School of Business at the University of Iowa. He received a Ph.D. in Mathematics from the University of Iowa in 1952, and an honorary doctorate from William Patterson College of New Jersey in 1979. His experience includes a year as a Fulbright Scholar at the University of Manchester, UK, ten years as a member of the New York University Graduate Center at Bell Labs, and ten years as a member of the IBM Systems Research Institute. He has held visiting faculty appointments at Columbia University, Dartmouth College, and the National University of Singapore, and has lectured and consulted internationally. He has authored or coauthored eight books on a variety of topics, including mathematics, probability, computer modeling, quality, and project management. He and Professor Ledolter are coauthors of the book Achieving Quality Through Continual Improvement, published by Wiley in 1999.

 

Introduction

Detecting and Prioritizing Problems

Problem-Solving Strategies

Group-Based Problem Solving

The Reward Structure: The Human Side of Problem Solving

Measurements and Their Importance for Quality

Analysis of Information: Graphical Displays and Numerical Summaries

Modeling Variability: An Introduction to Probability Distributions

Sample Surveys

Statistical Inference Under Simple Random Sampling

Acceptance Sampling Plans

Statistical Process Control: Control Charts

Process Capability and PRE-Control

Principles of Effective Experimental Design

Analysis of Data from Effective Experimental Designs and an Introduction to Factorial Experiments

Taguchi Design Methods for Product and Process Improvement

Regression Analysis: A Useful Tool for Modeling Relationships