Statistics for Engineering and the Sciences
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Imported Edition - Ships in 12-14 Days
Free Shipping in India on orders above Rs. 500
Prepare Your Students for Statistical Work in the Real World
Statistics for Engineering and the Sciences, Sixth Edition is designed for a two-semester introductory course on statistics for students majoring in engineering or any of the physical sciences. This popular text continues to teach students the basic concepts of data description and statistical inference as well as the statistical methods necessary for real-world applications. Students will understand how to collect and analyze data and think critically about the results.
New to the Sixth Edition
The first several chapters of the book identify the objectives of statistics, explain how to describe data, and present the basic concepts of probability. The text then introduces the two methods for making inferences about population parameters: estimation with confidence intervals and hypothesis testing. The remaining chapters extend these concepts to cover other topics useful in analyzing engineering and scientific data, including the analysis of categorical data, regression analysis, model building, analysis of variance for designed experiments, nonparametric statistics, statistical quality control, and product and system reliability.
William Mendenhall was a professor emeritus in the Statistics Department and the first chairman of the department at the University of Florida. Dr. Mendenhall published articles in top statistics journals and was a prolific author of statistics textbooks.
Terry L. Sincich is an associate professor in the Information Systems Decision Sciences Department at the University of South Florida, where he teaches introductory statistics at the undergraduate level and advanced statistics courses at the doctoral level. He has won numerous teaching awards, including the Kahn Teaching Award and Outstanding Teacher Award. Dr. Sincich is a member of the American Statistical Association and the Decision Sciences Institute. His research interests include applied statistical analysis and statistical modeling.
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