Applied Statistics for Engineers and Physical Scientists

by Ledolter, Johannes; Hogg, Robert V.

• ISBN13: 9780136017981
• ISBN10: 0136017983
• Edition: 3rd
• Format: Paperback
• Copyright: 2008-12-28
• Publisher: Pearson

Summary

This hugely anticipated revision has held true to its core strengths, while bringing the book fully up to date with modern engineering statistics. Written by two leading statisticians,Statistics for Engineers and Physical Scientists,3/e,provides the necessary bridge between basic statistical theory and interesting applications. Readers solve the same problems that engineers and scientists face, and have the opportunity to analyze real data sets. Larger-scale projects are a unique feature of this book, which let readers analyze and interpret real data, while also encouraging them to conduct their own studies and compare approaches and results. This book assumes a calculus background. Collection and Analysis of Information; Probability Models and Discrete Distributions; Continuous Probability Models; Statistical Inference: Sampling Distribution, Confidence Intervals, and Tests of Hypotheses; Statistical Process Control; Experiments with One Factor; Experiments with Two or More Factors; Regression Analysis. For all readers interested in applied statistics.

Author Biography

Johannes Ledolter is a Professor of Statistics and Actuarial Sciences at the University of Iowa as well as a C. Maxwell Stanley Professor of International Operations Management at the Henry B. Tippie College of Business. Ledolter received his M.S. and Ph.D. degrees in Statistics from the University of Wisconsin-Madison along with an M.S degree in Social and Economic Statistics from the University of Vienna. His research interests are in time series analysis, forecasting, and applied statistical modeling. His publications have appeared in Biometrika, Technometrics, Communications in Statistics, and Management Science. He is the co-author of several books including Experimental Design with Applications in Marketing and Service Operations, Introduction to Regression Modeling, Statistical Quality Control, and Statistical Methods for Forecasting.

 

 

Robert V. Hogg, Professor Emeritus of Statistics at the University of Iowa since 2001, received his B.A. in mathematics at the University of Illinois and his M.S. and Ph.D. degrees in mathematics, specializing in actuarial sciences and statistics, from the University of Iowa. Known for his gift of humor and his passion for teaching, Hogg has had far-reaching influence in the field of statistics. Throughout his career, Hogg has played a major role in defining statistics as a unique academic field, and he almost literally "wrote the book" on the subject. He has written more than 70 research articles and co-authored four books including  Introduction of Mathematical Statistics, 6^th edition, with J. W. McKean and  A.T. Craig,  as well as  Probability and Statistical Inference, 8^th edition and A Brief Course in Mathematical 1^st edition, both with E.A. Tanis. His texts have become classroom standards used by hundreds of thousands of students

 

Among the many awards he has received for distinction in teaching, Hogg has been honored at the national level (the Mathematical Association of America Award for Distinguished Teaching), the state level (the Governor's Science Medal for Teaching), and the university level (Collegiate Teaching Award). His important contributions to statistical research have been acknowledged by his election to fellowship standing in the ASA and the Institute of Mathematical Statistics.

Table of Contents

Normal 0 false false false

Collection and Analysis of Information

Introduction

Data Collection

Types of Data

The Study of Variability

Distributions

Importance of Variability (or Lack Thereof) for Quality and Productivity Improvement

Measurements Collected over Time

Time-Sequence Plots

Control Charts: A Special Case of Time-Sequence Plots

Data Display and Summary

Summary and Display of Measurement Data

Measures of Location

Measures of Variation

Exploratory Data Analysis: Stem-and-Leaf Displays and Box-and-Whisker Plots

Analysis of Categorical Data

Comparisons of Samples: The Importance of Stratification

Comparing Two Types of Wires

Comparing Lead Concentrations from Two Different Years

Number of Flaws for Three Different Products

Effects of Wind Direction on the Water Levels of Lake Neusiedl

Graphical Techniques, Correlation, and an Introduction to Least Squares

The Challenger Disaster

The Sample Correlations Coefficient as a Measure of Association in a Scatter Plot

Introduction to Least Squares

The Importance of Experimentation

Design of Experiments

Design of Experiments with Several Factors and the Determination of Optimum Conditions

Available Statistical Computer Software and the Visualization of Data

Computer Software

The Visualization of Da

Table of Contents provided by Publisher. All Rights Reserved.