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Stats Richard De Veaux

Stats By Richard De Veaux

Stats by Richard De Veaux


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Stats: Data and Models by Richard De Veaux

NOTE: You are purchasing a standalone product; MyStatLab does not come packaged with this content. If you would like to purchase both the physical text and MyStatLab search for: 0133956490 / 9780133956498 Stats: Data and Models Plus NEW MyStatLab with Pearson eText -- Access Card Package Package consists of: 0321847997 / 9780321847997 My StatLab Glue-in Access Card 032184839X / 9780321848390 MyStatLab Inside Sticker for Glue-In Packages 0321986490 / 9780321986498 Stats: Data and Models MyStatLab should only be purchased when required by an instructor. For one-or-two semester introductory statistics courses. Richard De Veaux, Paul Velleman, and David Bock wrote Stats: Data and Models with the goal that students and instructors have as much fun reading it as they did writing it. Maintaining a conversational, humorous, and informal writing style, this new edition engages students from the first page. The authors focus on statistical thinking throughout the text and rely on technology for calculations. As a result, students can focus on developing their conceptual understanding. Innovative Think/Show/Tell examples give students a problem-solving framework and, more importantly, a way to think through any statistics problem and present their results. The Fourth Edition is updated with instructor podcasts, video lectures, and new examples to keep material fresh, current, and relevant to today's students.

About Richard De Veaux

Richard 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. Since 1994, he has been Professor of Statistics at Williams College. 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. Dick is also well known in industry, where for more than 25 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. Dick is the father of four 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, and the Internet site Data and Story Library (DASL) (lib.stat.cmu.edu/DASL/), which provides data sets for teaching Statistics. Paul's understanding of using and teaching with technology informs much of this book's approach. Paul has taught Statistics at Cornell University since 1975. 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 two boys. 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 (three 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, serves as a Statistics consultant to the College Board, and leads workshops and institutes for AP Statistics teachers. He has recently served as K-12 Education and Outreach Coordinator and a senior lecturer for the Mathematics Department at Cornell University. His understanding of how students learn informs much of this book's approach. Dave and his wife relax by biking or hiking, spending much of their free time in Canada, the Rockies, or the Blue Ridge Mountains. They have a son, a daughter, and four grandchildren.

Table of Contents

Preface Part I: Exploring and Understanding Data 1. Stats Starts Here 1.1 What Is Statistics? 1.2 Data 1.3 Variables 2. Displaying and Describing Categorical Data 2.1 Summarizing and Displaying a Single Categorical variable 2.2 Exploring the Relationship Between Two Categorical variables 3. Displaying and Summarizing Quantitative Data 3.1 Displaying quantitative variables 3.2 Shape 3.3 Center 3.4 Spread 3.5 Boxplots and 5-Number Summaries 3.6 The Center of Symmetric Distributions: The Mean 3.7 The Spread of Symmetric Distributions: The Standard Deviation 3.8 Summary-What to Tell About a quantitative variable 4. Understanding and Comparing Distributions 4.1 Comparing Groups with Histograms 4.2 Comparing Groups with Boxplots 4.3 Outliers 4.4 Timeplots: Order, Please! 4.5 Re-Expressing Data: A First Look 5. The Standard Deviation as a Ruler and the Normal Model 5.1 Standardizing with z-Scores 5.2 Shifting and Scaling 5.3 Normal Models 5.4 Finding Normal Percentiles 5.5 Normal Probability Plots Part II: Exploring Relationships Between Variables 6. Scatterplots, Association, and Correlation 6.1 Scatterplots 6.2 Correlation 6.3 Warning: Correlation Causation 6.4 Straightening Scatterplots 7. Linear Regression 7.1 Least Squares: The Line of Best Fit 7.2 The Linear Model 7.3 Finding the Least Squares Line 7.4 Regression to the Mean 7.5 Examining the Residuals 7.6 R2-The variation Accounted For by the Model 7.7 Regression Assumptions and Conditions 8. Regression Wisdom 8.1 Examining Residuals 8.2 Extrapolation: Reaching Beyond the Data 8.3 Outliers, Leverage, and Influence 8.4 Lurking variables and Causation 8.5 Working with Summary values 9. Re-expressing Data: Get It Straight! 9.1 Straightening Scatterplots - The Four Goals 9.2 Finding a Good Re-Expression Part III: Gathering Data 10. Understanding Randomness 10.1 What Is Randomness? 10.2 Simulating by Hand 11. Sample Surveys 11.1 The Three Big Ideas of Sampling 11.2 Populations and Parameters 11.3 Simple Random Samples 11.4 Other Sampling Designs 11.5 From the Population to the Sample: You Can't Always Get What You Want 11.6 The valid Survey 11.7 Common Sampling Mistakes, or How to Sample Badly 12. Experiments and Observational Studies 12.1 Observational Studies 12.2 Randomized, Comparative Experiments 12.3 The Four Principles of Experimental Design 12.4 Control Treatments 12.5 Blocking 12.6 Confounding Part IV: Randomness and Probability 13. From Randomness to Probability 13.1 Random Phenomena 13.2 Modeling Probability 13.3 Formal Probability 14. Probability Rules! 14.1 The General Addition Rule 14.2 Conditional Probability and the General Multiplication Rule 14.3 Independence 14.4 Picturing Probability: Tables, Venn Diagrams, and Trees 14.5 Reversing the Conditioning and Bayes' Rule 15. Random Variables 15.1 Center: The Expected value 15.2 Spread: The Standard Deviation 15.3 Shifting and Combining Random variables 15.4 Continuous Random variables 16. Probability Models 16.1 Bernoulli Trials 16.2 The Geometric Model 16.3 The Binomial Model 16.4 Approximating the Binomial with a Normal Model 16.5 The Continuity Correction 16.6 The Poisson Model 16.7 Other Continuous Random Variables: The Uniform and the Exponential Part V: From the Data at Hand to the World at Large 17. Sampling Distribution Models 17.1 Sampling Distribution of a Proportion 17.2 When Does the Normal Model Work? Assumptions and Conditions 17.3 The Sampling Distribution of Other Statistics 17.4 The Central Limit Theorem: The Fundamental Theorem of Statistics 17.5 Sampling Distributions: A Summary 18. Confidence Intervals for Proportions 18.1 A Confidence Interval 18.2 Interpreting Confidence Intervals: What Does 95% Confidence Really Mean? 18.3 Margin of Error: Certainty vs. Precision 18.4 Assumptions and Conditions 19. Testing Hypotheses About Proportions 19.1 Hypotheses 19.2 P-values 19.3 The Reasoning of Hypothesis Testing 19.4 Alternative Alternatives 19.5 P-values and Decisions: What to Tell About a Hypothesis Test 20. Inferences About Means 20.1 Getting Started: The Central Limit Theorem (Again) 20.2 Gosset's t 20.3 Interpreting Confidence Intervals 20.4 A Hypothesis Test for the Mean 20.5 Choosing the Sample Size 21. More About Tests and Intervals 21.1 Choosing Hypotheses 21.2 How to Think About P-values 21.3 Alpha Levels 21.4 Critical values for Hypothesis Tests 21.5 Errors Part VI: Accessing Associations Between Variables 22. Comparing Groups 22.1 The Standard Deviation of a Difference 22.2 Assumptions and Conditions for Comparing Proportions 22.3 A Confidence Interval for the Difference Between Two Proportions 22.4 The Two Sample z-Test: Testing for the Difference Between Proportions 22.5 A Confidence Interval for the Difference Between Two Means 22.6 The Two-Sample t-Test: Testing for the Difference Between Two Means 22.7 The Pooled t-Test: Everyone into the Pool? 23. Paired Samples and Blocks 23.1 Paired Data 23.2 Assumptions and Conditions 23.3 Confidence Intervals for Matched Pairs 23.4 Blocking 24. Comparing Counts 24.1 Goodness-of-Fit Tests 24.2 Chi-Square Test of Homogeneity 24.3 Examining the Residuals 24.4 Chi-Square Test of Independence 25. Inferences for Regression 25.1 The Population and the Sample 25.2 Assumptions and Conditions 25.3 Intuition About Regression Inference 25.4 Regression Inference 25.5 Standard Errors for Predicted values 25.6 Confidence Intervals for Predicted values 25.7 Logistic Regression Part VII: Inference When Variables Are Related 26. Analysis of Variance 26.1 Testing Whether the Means of Several Groups Are Equal 26.2 The ANOVA Table 26.3 Assumptions and Conditions 26.4 Comparing Means 26.5 ANOVA on Observational Data 27. Multifactor Analysis of Variance 27.1 A Two Factor ANOVA Model 27.2 Assumptions and Conditions 27.3 Interactions 28. Multiple Regression 28.1 What Is Multiple Regression? 28.2 Interpreting Multiple Regression Coefficients 28.3 The Multiple Regression Model-Assumptions and Conditions 28.4 Multiple Regression Inference 28.5 Comparing Multiple Regression Models 29. Multiple Regression Wisdom 29.1 Indicators 29.2 Diagnosing Regression Models: Looking at the Cases 29.3 Building Multiple Regression Models 29.4 Building Multiple Regression Models Sequentially Appendixes A: Answers B: Photo Acknowledgments C: Index D: Tables and Selected Formulas

Additional information

CIN0321986490VG
9780321986498
0321986490
Stats: Data and Models by Richard De Veaux
Used - Very Good
Hardback
Pearson Education (US)
20150127
960
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in very good condition, but if you are not entirely satisfied please get in touch with us

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