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Statistics for Engineering and the Sciences by Terry Sincich and William Mendenhall (2006, Trade Paperback)
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Statistics for Engineering and the Sciences by Mendenhall, William; Sincich, Terry Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less
- Buy It NowStatistics for Engineering and the Sciences
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About this product
Product Identifiers
PublisherPrentice Hall PTR
ISBN-100131877062
ISBN-139780131877061
eBay Product ID (ePID)50807703
Product Key Features
Number of Pages1072 Pages
LanguageEnglish
Publication NameStatistics for Engineering and the Sciences
Publication Year2006
SubjectProbability & Statistics / General
FeaturesRevised
TypeTextbook
Subject AreaMathematics
AuthorTerry Sincich, William Mendenhall
FormatTrade Paperback
Dimensions
Item Height2.3 in
Item Weight74.9 Oz
Item Length9.9 in
Item Width8 in
Additional Product Features
Edition Number5
Intended AudienceCollege Audience
ReviewsReviewers Involved with the 5th Edition of "Statistics for Engineering and the Sciences: " Dharam Chopra (Wichita University) Edward Danial (Morgan State University) Frank Guess (University of Tennessee) Carol O'Connor Holloman (University of Louisville) Nancy Matthews (University of Oklahoma) Alan Rabideau (University of Bufffalo) Charles Reilly (University of Central Florida) Larry Ringer (Texas A&M University) Arnold Sweet (Purdue University) Paul Switzer (Stanford University) Reviewers of Previous Editions Carl Bodenschatz (United States Air Force Academy) George C. Derringer (Battelle Columbus, Ohio, Division) Danny Dyer (University of Texas-Arlington) Herberg Eisenberg (West Virginia College of Graduate Studies) Christopher Ennis (Normandale Community College) Nasrollah Etemadi (University of Illinois-Chicago) Linda Gans (California State Polytechnic University) Carol Gattis (University of Arkansas) K.G. Janardan (Eastern Michigan University) H. Lennon (Coventry Polytechnic, Coventry, England) Jeffery Maxey (University of Central Florida) Curtis McKnight (University of Oklahoma) Chand Midha (University of Akron) Balgobin Nandram (Worcester Polytechnic Institute) Paul Nelson (Kansas State University) Norbert Oppenheim (City College of New York) Giovanni Parmigiani (Duke University) David Powers (Clarkson University) David Robinson (St. Cloud State University) Shiva Saksena (University of North Carolina-Wilmington) Dennis Wackerly (University of Florida) Donald Woods (Texas A&M University), "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 havae been highlighted; real-life data has been extensively used throughout the book. Students will find it very appealing and u seful on their way to learning the basic statistical concepts and tools." - Dharam V. Chopra, Wichita State University "I like the problems in M& S-4 because they are all based on engineering applications of probability and statistics. I especially like the problems at the end of chapter 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." - Dr. Edward J. Danial, Morgan State University Reviewers Involved with the 5th Edition of "Statistics for Engineering and the Sciences: " Dharam Chopra (Wichita University) Edward Danial (Morgan State University) Frank Guess (University of Tennessee)Carol O' Connor Holloman (University of Louisville) Nancy Matthews (University of Oklahoma) Alan Rabideau (University of Bufffalo) Charles Reilly (University of Central Florida) Larry Ringer (Texas A& M University) Arnold Sweet (Purdue University) Paul Switzer (Stanford University) Reviewers of Previous Editions Carl Bodenschatz (United States Air Force Academy) George C. Derringer (Battelle Columbus, Ohio, Division) Danny Dyer (University of Texas-Arlington) Herberg Eisenberg (West Virginia College of Graduate Studies) Christopher Ennis (Normandale Community College) Nasrollah Etemadi (University of Illinois-Chicago)Linda Gans (California State Polytechnic University) Carol Gattis (University of Arkansas) K.G. Janardan (Eastern Michigan University) H. Lennon (Coventry Polytechnic, Coventry, England) Jeffery Maxey (University of Central Florida) Curtis McKnight (University of Oklahoma) Chand Midha (University of Akron) Balgobin Nandram (Worcester Polytechnic Institute) Paul Nelson (Kansas State University) Norbert Oppenheim (City College of New York) Giovanni Parmigiani (Duke University) David Powers (Clarkson University) David Robinson (St. Cloud State University) Shiva Saksena (University of North Carolina-Wilmington) DennisWackerly (University of Florida) Donald Woods (Texas A& M University), "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 havae been highlighted; real-life data has been extensively used throughout the book. Students will find it very appealing and u seful on their way to learning the basic statistical concepts and tools." - Dharam V. Chopra, Wichita State University "I like the problems in M&S-4 because they are all based on engineering applications of probability and statistics. I especially like the problems at the end of chapter 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." - Dr. Edward J. Danial, Morgan State University, "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 havae been highlighted; real-life data has been extensively used throughout the book. Students will find it very appealing and u seful on their way to learning the basic statistical concepts and tools." - Dharam V. Chopra, Wichita State University "I like the problems in M&S-4 because they are all based on engineering applications of probability and statistics. I especially like the problems at the end of chapter 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." - Dr. Edward J. Danial, Morgan State University Reviewers Involved with the 5th Edition ofStatistics for Engineering and the Sciences: Dharam Chopra (Wichita University) Edward Danial (Morgan State University) Frank Guess (University of Tennessee) Carol O'Connor Holloman (University of Louisville) Nancy Matthews (University of Oklahoma) Alan Rabideau (University of Bufffalo) Charles Reilly (University of Central Florida) Larry Ringer (Texas A&M University) Arnold Sweet (Purdue University) Paul Switzer (Stanford University) Reviewers of Previous Editions Carl Bodenschatz (United States Air Force Academy) George C. Derringer (Battelle Columbus, Ohio, Division) Danny Dyer (University of Texas-Arlington) Herberg Eisenberg (West Virginia College of Graduate Studies) Christopher Ennis (Normandale Community College) Nasrollah Etemadi (University of Illinois-Chicago) Linda Gans (Califor, "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 havae been highlighted; real-life data has been extensively used throughout the book. Students will find it very appealing and u seful on their way to learning the basic statistical concepts and tools." - Dharam V. Chopra, Wichita State University "I like the problems in M&S-4 because they are all based on engineering applications of probability and statistics. I especially like the problems at the end of chapter 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." - Dr. Edward J. Danial, Morgan State University , Reviewers Involved with the 5th Edition ofStatistics for Engineering and the Sciences: Dharam Chopra (Wichita University) Edward Danial (Morgan State University) Frank Guess (University of Tennessee) Carol O'Connor Holloman (University of Louisville) Nancy Matthews (University of Oklahoma) Alan Rabideau (University of Bufffalo) Charles Reilly (University of Central Florida) Larry Ringer (Texas A&M University) Arnold Sweet (Purdue University) Paul Switzer (Stanford University) Reviewers of Previous Editions Carl Bodenschatz (United States Air Force Academy) George C. Derringer (Battelle Columbus, Ohio, Division) Danny Dyer (University of Texas-Arlington) Herberg Eisenberg (West Virginia College of Graduate Studies) Christopher Ennis (Normandale Community College) Nasrollah Etemadi (University of Illinois-Chicago) Linda Gans (California State Polytechnic University) Carol Gattis (University of Arkansas) K.G. Janardan (Eastern Michigan University) H. Lennon (Coventry Polytechnic, Coventry, England) Jeffery Maxey (University of Central Florida) Curtis McKnight (University of Oklahoma) Chand Midha (University of Akron) Balgobin Nandram (Worcester Polytechnic Institute) Paul Nelson (Kansas State University) Norbert Oppenheim (City College of New York) Gio
Dewey Edition23
IllustratedYes
Dewey Decimal519.5
Edition DescriptionRevised edition
SynopsisThis text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of the physical sciences. Inevitably, once these students graduate and are employed, they will be involved in the collection and analysis of data and will be required to think critically about the results. Consequently, they need to acquire knowledge of the basic concepts of data description and statistical inference and familiarity with statistical methods they are required to use on the job., For engineering statistics courses in departments of Statistics and Engineering. This text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of the physical sciences. Inevitalby, once these studenrts graduate and are employed, they will be involved in the collection and analysis of data and will be required to think critically about the results. Consequently, they need to acquire knowledge of the basic concepts of data description and statistical inference and familiarity with statistical methods they are required to use on the job.The text includes optional theoretical exercises allowing instructors who choose to emphasize theory to do so without requiring additional materials. The assumed mathematical background is a two-semester sequence in calculus - that is, the course could be taught to students of average mathematical talent and with a basic understanding of the principles of differential and integral calculus. Datasets and other resources (where applicable) for this book are available here., This text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of the physical sciences. Inevitably, once these students graduate and are employed, they will be involved in the collection and analysis of data and will be required to think critically about the results. Consequently, they need to acquire knowledge of the basic concepts of data description and statistical inference and familiarity with statistical methods they are required to use on the job.
LC Classification NumberQA276.M429 2007
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Ratings and Reviews
Most relevant reviews
- Feb 24, 2016
It's a very good book
It's a great book. Easy to understand. Each section has a sample exercise to help the reader understand the section.Verified purchase: YesCondition: Pre-owned
