Annotated List of Exercises for
Statistical Modeling: A Fresh Approach

Daniel Kaplan

February 3, 2010

Contents

1 Chapter 1: Statistical Models
 1.1 Computing: Introduction to R
2 Chapter 2: Data
 2.1 Drills and Exercises
 2.2 In-Class Activities
 2.3 Computing in R
3 Chapter 3: Describing Variation
 3.1 Drills and Exercises
 3.2 Statistical Practice
 3.3 Computing
 3.4 Quick Quiz
 3.5 Class Activities
4 Chapter 4: The Language of Models
 4.1 Exercises
 4.2 Statistical Practice
 4.3 Elaborations
 4.4 Computation in R
5 Chapter 5: Model Formulas and Coefficients
 5.1 Exercises
 5.2 Statistical Practice
6 Chapter 6: Fitting Models to Data
 6.1 Exercises
 6.2 Statistical Practice
 6.3 Elaboration
7 Chapter 7: Measuring Correlation
 7.1 Exercises
 7.2 Statistical Practice
 7.3 Elaboration
 7.4 In-Class Activity
8 Chapter 8: Total and Partial Relationships
 8.1 Exercises
 8.2 Statistical Practice
 8.3 Elaborations
9 Chapter 9: Model Vectors
 9.1 Exercises
 9.2 Activities
10 Chapter 10: Statistical Geometry
 10.1 Exercises
 10.2 Elaborations
 10.3 Activities
11 Chapter 11: Geometry with Multiple Vectors
 11.1 Exercises
 11.2 Activities
12 Chapter 12: Modeling Randomness
 12.1 Exercises
13 Chapter 13: Geometry of Random Vectors
 13.1 Exercises
 13.2 Activities
14 Chapter 14: Confidence in Models
 14.1 Exercises
 14.2 Statistical Practice
 14.3 Computation in R
 14.4 Elaboration
 14.5 In-class Activities
15 Chapter 15: The Logic of Hypothesis Testing
 15.1 Exercises
 15.2 Statistical Practice
 15.3 Elaborations
 15.4 In-Class Activities
16 Chapter 16: Hypothesis Testing on Whole Models
 16.1 Exercises
 16.2 Statistical Practice
 16.3 Elaborations
 16.4 In-Class Activities
17 Chapter 17: Hypothesis Testing on Parts of Models
 17.1 Exercises
 17.2 In-Class Activity
 17.3 Statistical Practice
 17.4 Elaborations
18 Chapter 18: Models of Yes/No Variables
 18.1 Exercises
 18.2 Statistical Practice
19 Chapter 19: Causation
20 Chapter 20: Experiment
21 Review and Exam Problems
 21.1 R-Quiz
 21.2 Mid-Semester Review
 21.3 End of Semester Review
22 General Elaborations

At the start of the term:

1 Chapter 1: Statistical Models

This is an introductory chapter that sketches out broad concepts.

Chapter reading questions: ch1read

An analogy between models and scientific “laws”: 1.10,

1.1 Computing: Introduction to R

2 Chapter 2: Data

Chapter reading questions: ch2read

2.1 Drills and Exercises

2.2 In-Class Activities

2.3 Computing in R

3 Chapter 3: Describing Variation

Chapter reading questions: ch3read

3.1 Drills and Exercises

3.2 Statistical Practice

3.3 Computing

3.4 Quick Quiz

3.19, 3.20 [Need to modify]

3.5 Class Activities

4 Chapter 4: The Language of Models

Chapter reading questions: ch4read

4.1 Exercises

4.2 Statistical Practice

4.3 Elaborations

4.4 Computation in R

5 Chapter 5: Model Formulas and Coefficients

Chapter reading questions: ch5read

5.1 Exercises

5.2 Statistical Practice

6 Chapter 6: Fitting Models to Data

Chapter reading questions: ch6read

6.1 Exercises

6.2 Statistical Practice

6.3 Elaboration

7 Chapter 7: Measuring Correlation

Chapter reading questions: ch7read

Quick Quiz: 7.9

7.1 Exercises

7.2 Statistical Practice

7.3 Elaboration

7.4 In-Class Activity

8 Chapter 8: Total and Partial Relationships

Chapter reading questions: ch8read

8.1 Exercises

8.2 Statistical Practice

8.3 Elaborations

9 Chapter 9: Model Vectors

Chapter reading questions: ch9read

Graph paper and protractor/rulers at the same scale: http://www.macalester.edu/~kaplan/ISM/graph-paper.pdf. You can print out the first page on transparency paper to produce protractors for a class.

9.1 Exercises

9.2 Activities

10 Chapter 10: Statistical Geometry

Chapter reading questions: ch10read

10.1 Exercises

10.2 Elaborations

10.3 Activities

11 Chapter 11: Geometry with Multiple Vectors

Chapter reading questions: ch11read

11.1 Exercises

11.2 Activities

12 Chapter 12: Modeling Randomness

Chapter reading questions: ch12read

12.1 Exercises

Quick Quiz: 12.20,

Fun to show that intuition doesn’t correctly represent joint probabilities: 12.21 from Kahneman and Tversky

13 Chapter 13: Geometry of Random Vectors

Chapter reading questions: ch13read

13.1 Exercises

13.2 Activities

REDUNDANCY EXERCISE FROM 2009-10-08, s2009-29?

14 Chapter 14: Confidence in Models

Chapter reading questions: ch14read

14.1 Exercises

14.2 Statistical Practice

14.3 Computation in R

14.4 Elaboration

14.5 In-class Activities

15 Chapter 15: The Logic of Hypothesis Testing

Chapter reading questions: ch15read

15.1 Exercises

15.2 Statistical Practice

15.3 Elaborations

15.4 In-Class Activities

16 Chapter 16: Hypothesis Testing on Whole Models

Chapter reading questions: ch16read

16.1 Exercises

16.2 Statistical Practice

16.3 Elaborations

16.4 In-Class Activities

17 Chapter 17: Hypothesis Testing on Parts of Models

Chapter reading questions: ch17read

17.1 Exercises

17.2 In-Class Activity

17.3 Statistical Practice

17.4 Elaborations

18 Chapter 18: Models of Yes/No Variables

Chapter reading questions: ch18read

18.1 Exercises

18.2 Statistical Practice

19 Chapter 19: Causation

Chapter reading questions: ch19read

20 Chapter 20: Experiment

Chapter reading questions: ch20read

21 Review and Exam Problems

These problems combine materials from multiple chapters in a manner suitable for exams and other reviews.

INSTRUCTORS: A larger set of Review and Exam problems are available. Contact mailto:kaplan@macalester.edu.

21.1 R-Quiz

A quiz on basic operations in R. This is helpful in getting students to memorize the basic commands so that they can use them more fluently.

Quiz Study Guide: R-quiz-study-guide

The quiz itself, which is mainly a reprise of the study guide. Contact mailto:kaplan@macalester.edu.

21.2 Mid-Semester Review

Mid.3

21.3 End of Semester Review

A few problems .... Others are available to instructors upon request.

22 General Elaborations