Intermediate Statistical Investigations

896 Pages·2020·37.797 MB·English

by  Nathan Tintle, Beth L. Chance, Karen McGaughey, Soma Roy, Todd Swanson, Jill VanderStoep

Intermediate Statistical Investigations,
Enhanced eText
1. Cover
2. Nav
3. Cover
4. Title Page
5. Copyright
6. Dedication
7. About the Authors
8. Preface
9. Acknowledgments
10. Contents
11. PRELIMINARIES: Multivariable Thinking and Sources of
Variation
1. Preliminaries Overview
2. Preliminaries Summary
3. Preliminaries Glossary
4. Preliminaries Exercises
5. Preliminaries References
12. CHAPTER 1: Sources of Variation
1. Chapter Overview
2. SECTION 1.1 Sources of Variation in an Experiment
3. SECTION 1.2 Quantifying Sources of Variation
4. SECTION 1.3 Is the Variation Explained Statistically
Significant?
5. SECTION 1.4 Comparing Several Groups
6. SECTION 1.5 Confidence and Prediction Intervals
7. SECTION 1.6 More Study Design Considerations
8. Chapter 1 Summary
9. Chapter 1 Glossary
10. Chapter 1 Exercises
11. Chapter 1 Investigation
12. Chapter 1 References
13. CHAPTER 2: Controlling Additional Sources of Variation
1. Chapter Overview
2. SECTION 2.1 Paired Data
3. SECTION 2.2 Randomized Complete Block Designs
4. SECTION 2.3 Observational Study with Two Explanatory
Variables
5. Chapter 2 Summary
6. Chapter 2 Glossary
7. Chapter 2 Exercises
8. Chapter 2 Investigation
9. Chapter 2 References
14. CHAPTER 3: Multi-factor Studies and Interactions
1. Chapter Overview
2. SECTION 3.1 Multi-factor Experiments
3. SECTION 3.2 Statistical Interactions
4. SECTION 3.3 Replication
5. SECTION 3.4 Interactions in Observational Studies
6. Chapter 3 Summary
7. Chapter 3 Glossary
8. Chapter 3 Exercises
9. Chapter 3 Investigation
10. Chapter 3 References
15. CHAPTER 4: Including a Quantitative Explanatory Variable
1. Chapter Overview
2. SECTION 4.1 Quantitative Explanatory Variables
3. SECTION 4.2 Inference for Simple Linear Regression
4. SECTION 4.3 Quantitative and Categorical Explanatory
Variables
5. SECTION 4.4 Quantitative/Categorical Interactions
6. SECTION 4.5 Multi-level Categorical Variables
7. Chapter 4 Summary
8. Chapter 4 Glossary
9. Chapter 4 Exercises
10. Chapter 4 Investigation
11. Chapter 4 References
16. CHAPTER 5: Multiple Quantitative Explanatory Variables
1. Chapter Overview
2. SECTION 5.1: Experiments with Multiple Quantitative
Explanatory Variables
3. SECTION 5.2: Observational Studies with Multiple
Quantitative Explanatory Variables
4. SECTION 5.3: Modeling Nonlinear Associations Part I—
Polynomial Models
5. SECTION 5.4: Modeling Nonlinear Associations Part II—
Transformations
6. Chapter 5 Summary
7. Chapter 5 Glossary
8. Chapter 5 Exercises
9. Chapter 5 Investigation
10. Chapter 5 References
17. CHAPTER 6: Categorical Response Variable
1. Chapter Overview
2. SECTION 6.1 Comparing Proportions
3. SECTION 6.2 Introduction to Logistic Regression
4. SECTION 6.3 Multiple Logistic Regression Models
5. Chapter 6 Summary
6. Chapter 6 Glossary
7. Chapter 6 Exercises
8. Chapter 6 Investigation
9. Chapter 6 References
18. CHAPTER 7: Practical Issues
1. Chapter Overview
2. SECTION 7.1 Dealing with the Messes Created by Messy
Data
3. SECTION 7.2 Multiple Regression with Many
Explanatory Variables
4. Chapter 7 Summary
5. Chapter 7 Glossary
19. Index
20. End User License Agreement

Intermediate Statistical
Investigations
NATHAN L. TINTLE
Dordt University
BETH L. CHANCE
California Polytechnic State University
KAREN MCGAUGHEY
California Polytechnic State University
SOMA ROY
California Polytechnic State University
TODD M. SWANSON
Hope College
JILL L. VANDERSTOEP
Hope College
Laurie
VICE PRESIDENT & DIRECTOR
Rosatone
EXECUTIVE EDITOR Joanna Dingle
SENIOR COURSE CONTENT
Kim Eskin
DEVELOPER
SENIOR MANAGER COURSE Svetlana
DEVELOPMENT AND PRODUCTION Barskaya
SENIOR COURSE PRODUCTION Ashley
OPERATIONS SPECIALIST Patterson
EXECUTIVE MANAGING EDITOR Valerie Zaborski
LEAD PRODUCT DESGINER Tom Kulesa
Mike
MARKETING MANAGER
MacDougald
CREATIVE PRODUCT DESIGN LEAD Jon Boylan
SENIOR CREATIVE PRODUCT
Wendy Lai
DESIGNER
EDITORIAL ASSISTANT Hannah Larkin
COVER DESIGNER Wendy Lai
©
COVER PHOTO berkpixels/Getty
Images
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This project has been and is being supported from the National
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Library of Congress Cataloging-in-Publication Data
Names: Tintle, Nathan, author. | Chance, Beth L., author. |
McGaughey, Karen, author. | Roy, Soma, author. | Swanson, Todd,
author. | VanderStoep, Jill, author.
Title: Intermediate statistical investigations / Nathan L. Tintle, Beth L.
Chance, Karen McGaughey, Soma Roy, Todd M. Swanson, Jill L.
VanderStoep.
Description: Hoboken, NJ : Wiley, [2021] | Includes index.
Identifiers: LCCN 2020014465 (print) | LCCN 2020014466 (ebook) |
ISBN 9781119634522 (paperback) | ISBN 9781119681717 (adobe
pdf) | ISBN 9781119634423 (epub)
Subjects: LCSH: Social sciences—Statistical methods. | Statistical
hypothesis testing.
Classification: LCC HA29 .T559 2021 (print) | LCC HA29 (ebook) |
DDC 001.4/22—dc23
LC record available at https://lccn.loc.gov/2020014465
LC ebook record available at https://lccn.loc.gov/2020014466
ISBN: 9781119634423
Dedication
We dedicate this textbook to George Cobb (1947-2020), who was an
inspiration to so many in the statistics education community. He
eloquently pushed us and others to teach statistics in ways that have
benefited hundreds of thousands of students. His intelligence,
thoughtfulness, and humor flowed through his writing. The guidance
and wisdom he provided us as we conceptualized and developed this
textbook was immeasurable. He will be greatly missed as both a
colleague and a friend.
George’s eloquence is captured in the following analogy, which serves
as a continued motivation for us to teach statistics differently and to
help students complete our courses with an understanding that
statistics is a beautiful way to make sense of the world in which we
live.
Few students typically leave a statistics course thinking of Statistics as
a beautiful cathedral.