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STAT2
with Premium Access CardFirst Edition| ©2014 Ann R. Cannon; George W. Cobb; Bradley A. Hartlaub; Julie M. Legler; Robin H. Lock; Thomas L. Moore; Allan J. Rossman; Jeffrey A. Witmer
1. Choose the appropriate statistical model for a particular problem.
2. Know the conditions that are typically required when fitting various models.
3. Assess whether or not the conditions for a particular model are reasonably met for a specific dataset. 4. Have some strategies for dealing with data when the conditions for a standard model are not met.
5. Use the appropriate model to make appropriate inferences.
1. Choose the appropriate statistical model for a particular problem.
2. Know the conditions that are typically required when fitting various models.
3. Assess whether or not the conditions for a particular model are reasonably met for a specific dataset. 4. Have some strategies for dealing with data when the conditions for a standard model are not met.
5. Use the appropriate model to make appropriate inferences.
Features
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. For a class with strong backgrounds, instructors may choose to move more quickly through the first three chapters, treating that material mostly as review for students to get back up “to speed.”
Flexibility Within and Between Units
The chapters and units are arranged to 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.
New to This Edition
STAT2 is being class tested at schools throughout the country and heres what students are saying:“Its probably one of the clearest math, science, and engineering textbooks around.”
Senior Engineering/Economics major, Smith College
“I like this textbook because its straight to the point and does not include a lot of fluffing up of the material.”
Sophomore Biochemistry/Molecular Biology/Psychology major, Cornell College“It reads like somebody is talking to you.”
Senior Biochemistry major, Smith College“Well-written, goes into great detail with concepts and includes cool examples and exercises that spark the readers interest.”
- Junior Math major, St Lawrence University“Logistic regression and two-way ANOVA were very challenging, but the text provided examples and it was easy to understand what the text was interpreting in each.”
Sophomore Psychology major, St Lawrence University
STAT2
First Edition| ©2014
Ann R. Cannon; George W. Cobb; Bradley A. Hartlaub; Julie M. Legler; Robin H. Lock; Thomas L. Moore; Allan J. Rossman; Jeffrey A. Witmer
Digital Options
STAT2
First Edition| 2014
Ann R. Cannon; George W. Cobb; Bradley A. Hartlaub; Julie M. Legler; Robin H. Lock; Thomas L. Moore; Allan J. Rossman; Jeffrey A. Witmer
Table of Contents
0 What Is a Statistical Model?
0.1 Fundamental Terminology
0.2 Four-Step Process
0.3 Chapter Summary
0.4 Exercises
Unit A: Linear Regression
1 Simple Linear Regression
1.1 The Simple Linear Regression Model
1.2 Conditions for a Simple Linear Model
1.3 Assessing Conditions
1.4 Transformations
1.5 Outliers & Influential Points
1.6 Chapter Summary
1.7 Exercises
2 Inference for Simple Linear Regression
2.1 Inference for Regression Slope
2.2 Partitioning Variability - ANOVA
2.3 Regression and Correlation
2.4 Intervals for Predictions
2.5 Chapter Summary
2.6 Exercises
3 Multiple Regression
3.1 Multiple Linear Regression Model
3.2 Assessing a Multiple Regression Model
3.3 Comparing Two Regression Lines
3.4 New Predictors from Old
3.5 Correlated Predictors
3.6 Testing Subsets of Predictors
3.7 Case Study: Predicting in Retail Clothing
3.8 Chapter Summary
3.9 Exercises
4 Additional Topics in Regression
4.1 Topic: Added Variable Plots
4.2 Topic: Techniques for Choosing Predictors
4.3 Topic: Identifying Unusual Points in Regression
4.4 Topic: Coding Categorical Predictors
4.5 Topic: Randomization Test for a Relationship
4.6 Topic: Bootstrap for Regression
4.7 Exercises
Unit B: Analysis of Variance
5 One-way ANOVA
5.1 The One-way Model: Comparing Groups
5.2 Assessing and Using the Model
5.3 Scope of Inference
5.4 Fisher’s Least Significant Difference
5.5 Chapter Summary
5.6 Exercises
6 Multifactor ANOVA
6.1 The Two-way Additive Model (Main Effects Model)
6.2 Interaction in the Two-way Model
6.3 The Two-way Non-additive Model (Two-Way ANOVA with Interaction)
6.4 Case Study
6.5 Chapter Summary
6.6 Exercises
7 Additional Topics in Analysis of Variance
7.1 Topic: Levene’s Test for Homogeneity of Variances
7.2 Topic: Multiple Tests
7.3 Topic: Comparisons and Contrasts
7.4 Topic: Nonparametric Statistics
7.5 Topic: ANOVA and Regression with Indicators
7.6 Topic: Analysis of Covariance
7.7 Exercises
8 Overview of Experimental Design
8.1 Comparisons and Randomization
8.2 Randomization F Test
8.3 Design Strategy: Blocking
8.4 Design Strategy: Factorial Crossing
8.5 Chapter Summary
8.6 Exercises
Unit C: Logistic Regression
9 Logistic Regression
9.1 Choosing a Logistic Regression Model
9.2 Logistic regression and odds ratios
9.3 Assessing the logistic regression model
9.4 Formal inference: tests and intervals
9.5 Summary
9.6 Exercises
10 Multiple Logistic Regression
10.1 Overview
10.2 Choosing, fitting, and interpreting models
10.3 Checking conditions
10.4 Formal inference: tests and intervals
10.5 Case Study: Bird Nests
10.6 Summary
10.7 Exercises
11 Additional Topics in Logistic Regression
11.1 Topic: Fitting the logistic regression model
11.2 Topic: Assessing Logistic Regression Models
11.3 Randomization Tests
11.4 Analyzing Two-way Tables with Logistic Regression
11.5 Exercises
STAT2
First Edition| 2014
Ann R. Cannon; George W. Cobb; Bradley A. Hartlaub; Julie M. Legler; Robin H. Lock; Thomas L. Moore; Allan J. Rossman; Jeffrey A. Witmer
Authors
Ann Cannon
George W. Cobb
Bradley A. Hartlaub
Julie M. Legler
Robin H. Lock
Thomas L. Moore
Allan J. Rossman
Allan J. Rossman is Professor and Chair of the Statistics Department at Cal Poly – San Luis Obispo. He served as Chief Reader of the Advanced Placement program in Statistics from 2009-2014. He was Program Chair for the 2007 Joint Statistical Meetings and for the U.S. Conference in Teaching Statistics since 2013. He is a Fellow of the American Statistical Association and has received the Mathematical Association of America’s Haimo Award for Distinguished College or University Teaching of Mathematics and the ASA’s Waller Distinguished Teaching Career Award.
Jeffrey A. Witmer
STAT2
First Edition| 2014
Ann R. Cannon; George W. Cobb; Bradley A. Hartlaub; Julie M. Legler; Robin H. Lock; Thomas L. Moore; Allan J. Rossman; Jeffrey A. Witmer
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STAT2
First Edition| 2014
Ann R. Cannon; George W. Cobb; Bradley A. Hartlaub; Julie M. Legler; Robin H. Lock; Thomas L. Moore; Allan J. Rossman; Jeffrey A. Witmer
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