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    Akzeptabel: Buch mit deutlichen Gebrauchsspuren. Der Einband kann einige Beschädigungen aufweisen, ...
    Release Year
    2006
    Book Title
    Statistics for Engineering and the Sciences
    ISBN
    9780131877061

    Über dieses Produkt

    Product Identifiers

    Publisher
    Prentice Hall PTR
    ISBN-10
    0131877062
    ISBN-13
    9780131877061
    eBay Product ID (ePID)
    50807703

    Product Key Features

    Number of Pages
    1072 Pages
    Language
    English
    Publication Name
    Statistics for Engineering and the Sciences
    Publication Year
    2006
    Subject
    Probability & Statistics / General
    Features
    Revised
    Type
    Textbook
    Subject Area
    Mathematics
    Author
    Terry Sincich, William Mendenhall
    Format
    Trade Paperback

    Dimensions

    Item Height
    2.3 in
    Item Weight
    74.9 Oz
    Item Length
    9.9 in
    Item Width
    8 in

    Additional Product Features

    Edition Number
    5
    Intended Audience
    College Audience
    Reviews
    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) 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 Edition
    23
    Illustrated
    Yes
    Dewey Decimal
    519.5
    Edition Description
    Revised edition
    Synopsis
    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., 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 Number
    QA276.M429 2007

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