Inbunden, Engelska, 2015

Statistics for Engineering and the Sciences

Av William M. Mendenhall, Terry L. Sincich

1596 kr

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Beskrivning

Prepare Your Students for Statistical Work in the Real WorldStatistics 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 EditionMany new and updated exercises based on contemporary engineering and scientific-related studies and real dataMore statistical software printouts and corresponding instructions for use that reflect the latest versions of the SAS, SPSS, and MINITAB softwareIntroduction of the case studies at the beginning of each chapterStreamlined material on all basic sampling concepts, such as random sampling and sample survey designs, which gives students an earlier introduction to key sampling issuesNew examples on comparing matched pairs versus independent samples, selecting the sample size for a designed experiment, and analyzing a two-factor experiment with quantitative factorsNew section on using regression residuals to check the assumptions required in a simple linear regression analysisThe 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.

Produktinformation

Utgivningsdatum: 2015-12-16
Mått: 203 x 254 x 52 mm
Vikt: 2 271 g
Format: Inbunden
Språk: Engelska
Antal sidor: 1 166
Upplaga: 6
Förlag: Taylor & Francis Inc
ISBN: 9781498728850

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Mer om författaren

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.

Recensioner i media

"A salient feature of this book is the clarity with which many statistical concepts have been presented. A very nice blend of theory and applications. It contains a wealth of illustrative examples and problem sets. All the important concepts have been highlighted; real-life data has been extensively used throughout the book. Students will find it very appealing and useful on their way to learning the basic statistical concepts and tools."—Dharam V. Chopra, Wichita State University"I like the problems because they are all based on engineering applications of probability and statistics. I especially like the problems at the end of chapters because students have to think more to solve them. I favor problems that require calculations because engineers are problem solvers." —Charles H. Reilly, University of Central Florida"I think this text is one of the best I have seen when it comes down to real data sets. The authors successfully included small and large real data sets from various real-world problems in engineering, mathematical sciences, and natural sciences."—Edward J. Danial, Morgan State University

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