About our authorsRichard D. DeVeaux 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 theacapellagroup 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 (twice), 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.

Texte du rabat

For courses in Introductory Statistics.

Uses innovative methods, technology, and humor to encourage statistical thinking

Intro Stats, 6th Edition by De Veaux/Velleman/Bock uses inventive strategies to help students think critically about data, while maintaining the book's core concepts, coverage, and readability. By using technology and simulations to demonstrate variability at critical points throughout the course, the authors make it easier for instructors to teach and for students to understand more complicated statistical concepts later in the course.

This revision includes several enhancements, enriching material with greater use of the authors' signature tools for teaching about randomness, sampling distribution models, and inference. Current discussions of ethical issues have been added throughout, and each chapter now ends with a student project that can be used for collaborative work.

This title is also available digitally as a standalone Pearson eText, or via MyLab Statistics, which includes the Pearson eText. Contact your Pearson rep for more information.

MyLab® empowers you to reach every student. This flexible digital platform combines unrivaled content, online assessments, and customizable features so you can personalize learning and improve results. Learn more about MyLab Statistics.

Pearson eText is an easy-to-use digital textbook available within MyLab Statistics that lets students read, highlight, take notes, and review key vocabulary all in one place. For instructors not using MyLab Statistics, Pearson eText can also be adopted on its own as the main course material. Learn more about Pearson eText.

Contenu

Indicates optional section I: EXPLORING AND UNDERSTANDING DATA

Stats Starts Here
- 1.1 What Is Statistics?
- 1.2 Data
- 1.3 Variables
- 1.4 Models
Displaying and Describing Data
- 2.1 Summarizing and Displaying a Categorical Variable
- 2.2 Displaying a Quantitative Variable
- 2.3 Shape
- 2.4 Center
- 2.5 Spread
Relationships Between Categorical Variables: Contingency Tables
- 3.1 Contingency Tables
- 3.2 Conditional Distributions
- 3.3 Displaying Contingency Tables
- 3.4 Three Categorical Variables
Understanding and Comparing Distributions
- 4.1 Displays for Comparing Groups
- 4.2 Outliers
- 4.3 Re-Expressing Data: A First Look
The Standard Deviation as a Ruler and the Normal Model
- 5.1 Using the standard deviation to Standardize Values
- 5.2 Shifting and Scaling
- 5.3 Normal Models
- 5.4 Working with Normal Percentiles
- 5.5 Normal Probability Plots
- Review of Part I: Exploring and Understanding DataII: EXPLORING RELATIONSHIPS BETWEEN VARIABLESScatterplots, Association, and Correlation