This text provides a rigorous introduction to basic probability theory and statistical inference that is motivated by interesting, relevant applications. It assumes a background in calculus and offers a balance of theory and methodology. Features of the publication include complete detailed case studies, an updated discussion of hypothesis testing and excercise sets. It is aimed at junior/senior undergraduates studying engineering, science or computer science.
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Raymond H Myers is currently Professor Emeritus of statistics at Virginia Tech. He received his Masters and Ph.D. from Virginia Tech in statistics and his BS in chemical engineering. His major areas of interest are linear models, design of experiments, and response surface methodology. He has authored or co-authored six statistics texts that were published in fifteen separate editions and in several foreign languages.
He has received numerous teaching awards and in 1985 he was selected “Professor of the Year” in the state of Virginia by the Council on the Advancement and Support of Education. He was elected Fellow of ASA in 1974. In 1999 he was given the Shewhart Award for lifetime contributions in statistics and quality control by the American Society of Quality.
Sharon L Myers
is currently Professor Emeritus of mathematics and statistics at Radford University. She received her MS in statistics from Virginia Tech. Her areas of interest are statistical computing, regression analysis, and response surface methodology. She has co-authored three editions of “Probability & Statistics for Engineers & Scientists”. She was the assistant director of the statistical consulting center at Virginia Tech for 15 years and the director of the statistical consulting center at Radford University for 7 years.
Keying Ye, University of Texas at San Antonio
For junior/senior undergraduates studying engineering, science or computer science.
This classic text provides a rigorous introduction to basic probability theory and statistical inference that is motivated by interesting, relevant applications. Assumes a background in calculus; offers a unique balance of theory and methodology.
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