©2014

STAT2

with Premium Access Card

Ann R. Cannon (Cornell College) , George W. Cobb (Mount Holyoke College) , Bradley A. Hartlaub (Kenyon College) , Julie M. Legler (St. Olaf College) , Robin H. Lock (St. Lawrence University) , Thomas L. Moore (Grinnell College) , Allan J. Rossman (California Polytechnic State University) , Jeffrey A. Witmer (Oberlin College)

  • ISBN-10: 1-4641-4826-0; ISBN-13: 978-1-4641-4826-2; Format: Quantity Pack

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