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Applied Statistics for Engineers and Physical Scientists,9780136017981
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Applied Statistics for Engineers and Physical Scientists

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This is the 3rd edition with a publication date of 12/28/2008.
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  • Applied Statistics for Engineers and Physical Scientists
    Applied Statistics for Engineers and Physical Scientists


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, 6th edition, with J. W. McKean and  A.T. Craig,  as well as  Probability and Statistical Inference, 8th edition and A Brief Course in Mathematical 1st 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

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Collection and Analysis of Information
Data Collection
Types of Data
The Study of Variability
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.

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