Stats: Data and Models, Global Edition

Häftad, Engelska, 2021

AvRichard De Veaux,Paul Velleman,David Bock

1 089 kr

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For courses in Introductory Statistics.
Encourages statistical thinking using technology, innovative methods, and a sense of humour
Inspired by the 2016 GAISE Report revision, Stats: Data and Models, 5th Edition by De Veaux, Velleman, and Bock uses innovative strategies to help students think critically about data, while maintaining the book's core concepts, coverage, and most importantly, readability.
The authors make it easier for instructors to teach and for students to understand more complicated statistical concepts later in the course (such as the Central Limit Theorem). In addition, students get more exposure to large data sets and multivariate thinking, which better prepares them to be critical consumers of statistics in the 21st century.
The 5th Edition’s approach to teaching Stats: Data and Models is revolutionary, yet it retains the book's lively tone and hallmark pedagogical features such as its Think/Show/Tell Step-by-Step Examples.

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Produktinformation

Utgivningsdatum2021-04-28
Mått379 x 219 x 42 mm
Vikt2 148 g
FormatHäftad
SpråkEngelska
SeriePearson Education Limited
Antal sidor1 024
Upplaga5
FörlagPearson Education
ISBN9781292362212

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About our authors Richard D. De Veaux is an internationally known educator and consultant. He has taught at the Wharton School and the Princeton University School of Engineering, where he won a Lifetime Award for Dedication and Excellence in Teaching. He is the C. Carlisle and M. Tippit Professor of Statistics at Williams College, where he has taught since 1994. Dick has won both the Wilcoxon and Shewell awards from the American Society for Quality. He is a fellow of the American Statistical Association (ASA) and an elected member of the International Statistical Institute (ISI). In 2008, he was named Statistician of the Year by the Boston Chapter of the ASA, and was the 2018-2021 Vice-President of the ASA. Dick is also well known in industry, where for more than 30 years he has consulted for such Fortune 500 companies as American Express, Hewlett-Packard, Alcoa, DuPont, Pillsbury, General Electric, and Chemical Bank. Because he consulted with Mickey Hart on his book Planet Drum, he has also sometimes been called the "Official Statistician for the Grateful Dead." His real-world experiences and anecdotes illustrate many of this book's chapters. Dick holds degrees from Princeton University in Civil Engineering (B.S.E.) and Mathematics (A.B.) and from Stanford University in Dance Education (M.A.) and Statistics (Ph.D.), where he studied dance with Inga Weiss and Statistics with Persi Diaconis. His research focuses on the analysis of large data sets and data mining in science and industry. In his spare time, he is an avid cyclist and swimmer. He also is the founder of the "Diminished Faculty," an a cappella Doo-Wop quartet at Williams College, and sings bass in the college concert choir and with the Choeur Vittoria of Paris. Dick is the father of 4 children. Paul F. Velleman has an international reputation for innovative Statistics education. He is the author and designer of the multimedia Statistics program ActivStats, for which he was awarded the EDUCOM Medal for innovative uses of computers in teaching statistics, and the ICTCM Award for Innovation in Using Technology in College Mathematics. He also developed the award-winning statistics program Data Desk, the Internet site Data and Story Library (DASL) which provides data sets for teaching Statistics, and the tools referenced in the text for simulation and bootstrapping. Paul's understanding of using and teaching with technology informs much of this book's approach. Paul taught Statistics at Cornell University, where he was awarded the MacIntyre Award for Exemplary Teaching. He is Emeritus Professor of Statistical Science from Cornell and lives in Maine with his wife, Sue Michlovitz. He holds an A.B. from Dartmouth College in Mathematics and Social Science, and M.S. and Ph.D. degrees in Statistics from Princeton University, where he studied with John Tukey. His research often deals with statistical graphics and data analysis methods. Paul co-authored (with David Hoaglin) ABCs of Exploratory Data Analysis. Paul is a Fellow of the American Statistical Association and of the American Association for the Advancement of Science. Paul is the father of 2 boys. In his spare time he sings with the acapella group VoXX and studies tai chi. David E. Bock taught mathematics at Ithaca High School for 35 years. He has taught Statistics at Ithaca High School, Tompkins-Cortland Community College, Ithaca College, and Cornell University. Dave has won numerous teaching awards, including the MAA's Edyth May Sliffe Award for Distinguished High School Mathematics Teaching (2 times), Cornell University's Outstanding Educator Award (3 times), and has been a finalist for New York State Teacher of the Year. Dave holds degrees from the University at Albany in Mathematics (B.A.) and Statistics/Education (M.S.). Dave has been a reader and table leader for the AP Statistics exam and a Statistics consultant to the College Board, leading workshops and institutes for AP Statistics teachers. His understanding of how students learn informs much of this book's approach.

I: EXPLORING AND UNDERSTANDING DATA 1. Stats Starts Here2. Displaying and Describing Data3. Relationships Between Categorical Variables–Contingency Tables4. Understanding and Comparing Distributions5. The Standard Deviation as a Ruler and the Normal ModelII. EXPLORING RELATIONSHIPS BETWEEN VARIABLES 6. Scatterplots, Association, and Correlation7. Linear Regression8. Regression Wisdom9. Multiple RegressionIII. GATHERING DATA 10. Sample Surveys11. Experiments and Observational StudiesIV. RANDOMNESS AND PROBABILITY 12. From Randomness to Probability13.Probability Rules!14. Random Variables15. Probability ModelsV. INFERENCE FOR ONE PARAMETER 16. Sampling Distribution Models and Confidence Intervals for Proportions17. Confidence Intervals for Means18. Testing Hypotheses19. More About Tests and IntervalsVI. INFERENCE FOR RELATIONSHIPS 20. Comparing Groups21. Paired Samples and Blocks22. Comparing Counts23. Inferences for RegressionVII. INFERENCE WHEN VARIABLES ARE RELATED 24. Multiple Regression Wisdom25. Analysis of Variance26. Multifactor Analysis of Variance27. Statistics and Data Science