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STAT 2

Building Models for a World of Data

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WH Freeman

Pages: 648
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Hardcover - 9781464148262

14 December 2012

€75.96

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STAT2 offers students who have taken AP Statistics or a typical introductory statistics college level course to the opportunity to learn more sophisticated concepts and the tools with which to apply them. The book helps...

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STAT2 offers students who have taken AP Statistics or a typical introductory statistics college level course to the opportunity to learn more sophisticated concepts and the tools with which to apply them. The book helps students gain facility in the use of common statistical models..  The chapters are grouped to consider models based on the type of response and type of predictors.

After completing a course with STAT2 students should be able to choose the appropriate statistical model for a particular problem, know the conditions that are typically required when fitting various models, and use the appropriate model to make appropriate inferences. This textbook is also available on LaunchPad, an innovative online resource designed to engage students and help instructors.

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  • Available on LaunchPad, which provides students with everything they need to prepare for class and exams. For instructors, LaunchPad offers everything you need to quickly set up a course, customize the content to their syllabus, craft presentations and lectures, assign and assess readings and activities, and much more.
  • Students will come to a second course with different backgrounds and levels of experience. Instructors can repeat some material from the first course as they find appropriate, possibly in a slightly different setting.
  • The chapters and units promote flexibility in the order and depth in which topics are covered. Within a unit, some instructors may choose to "splice" in an additional topic when those ideas are first introduced. Instructors can also adjust the order of topics between the units.

0 What Is a Statistical Model?
Unit A: Linear Regression 1 Simple Linear Regression
2 Inference for Simple Linear Regression
3 Multiple Regression
4 Additional Topics in Regression
Unit B: Analysis of Variance 5 One-way ANOVA
6 Multifactor ANOVA
7 Additional Topics in Analysis of Variance
8 Overview of Experimental Design
Unit C: Logistic Regression
9 Logistic Regression
10 Multiple Logistic Regression
11 Additional Topics in Logistic Regression 




 
 



 

 






You can access this textbook on LaunchPad. With LaunchPad, you’ll have access to an interactive eBook with multimedia content. You’ll also be able to benefit from its adaptive quizzing and learning tools which will help you succeed in your course. Purchase your LaunchPad access card or print and LaunchPad bundle above.

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Ann R. Cannon has been a faculty member at Cornell College since 1993. She is currently Professor of Statistics in the Department of Mathematics and Statistics. 


George Cobb is Robert l. Rooke Professor emeritus at Mount Holyoke College, where he taught from 1974 to 2009 after earning his PhD in statistics from Harvard University.

Brad Hartlaub joined the faculty of Kenyon College, Minnesota in 1990. He is a nonparametric statistician, and his research deals with rank-based tests for detecting interaction.

Julie Legler is Professor of Statistics and Director of the Statistics Program at St. Olaf College in Minnesota.

Robin H. Lock is the Jack and Sylvia Burry Professor of Statistics at St. Lawrence University where...

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Ann R. Cannon has been a faculty member at Cornell College since 1993. She is currently Professor of Statistics in the Department of Mathematics and Statistics. 


George Cobb is Robert l. Rooke Professor emeritus at Mount Holyoke College, where he taught from 1974 to 2009 after earning his PhD in statistics from Harvard University.

Brad Hartlaub joined the faculty of Kenyon College, Minnesota in 1990. He is a nonparametric statistician, and his research deals with rank-based tests for detecting interaction.

Julie Legler is Professor of Statistics and Director of the Statistics Program at St. Olaf College in Minnesota.

Robin H. Lock is the Jack and Sylvia Burry Professor of Statistics at St. Lawrence University where he has taught since 1983 after receiving his PhD from the University of Massachusetts- Amherst.

Thomas Moore is a Fellow of American Statistical Association and was the2008 Mu Sigma Rho Statistical Education Award winner.

Allan J. Rossman is Professor of Statistics at Cal Poly – San Luis Obispo and previously taught in the Department of Mathematics and Computer Science at Dickinson College, Pennsylvania.

Jeff Witmer is Professor of Mathematics at Oberlin College, Ohio and is a Fellow of the American Statistical Association.

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