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ISCAM: Investigating Statistical Concepts, Applications, and Methods
Beth L. Chance, Allan J. Rossman
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Front Matter
To the Student
Using Technology with This Book
1
Preliminaries
1.1
Distributions and Variability
1.1.1
Investigation A: Hurricanes and Climate Change
1.1.2
Practice Problem A.A
1.2
Randomness and Probability
1.2.1
Investigation B: Random Babies
1.2.2
Practice Problem B.A
1.2.3
Practice Problem B.B
1.2.4
Practice Problem B.C
1.3
Modelling
1.3.1
Investigation C: Modelling Hurricanes
1.3.2
Practice Problem C.A
1.3.3
Practice Problem C.B
2
ISCAM
Ch. 1 Intro
3
Analyzing a Process Probability
3.1
Investigation 1.1: Friend or Foe?
3.1.1
The Study
3.1.2
Practice Problem 1.1A
3.1.3
Practice Problem 1.1B
3.2
Investigation 1.2: Can Wolves Understand Human Cues?
3.2.1
The Study
3.2.2
Practice Problem 1.2A
3.2.3
Practice Problem 1.2B
3.3
Investigation 1.3: Are You Clairvoyant?
3.3.1
The Scenario
3.3.2
Practice Problem 1.3A
3.3.3
Practice Problem 1.3B
3.3.4
Practice Problem 1.3C
3.4
Investigation 1.4: Heart Transplant Mortality
3.4.1
The Study
3.4.2
Practice Problem 1.4A
3.4.3
Practice Problem 1.4B
3.4.4
Practice Problem 1.4C
3.5
Investigation 1.5: Buttered Side Down Again?
3.5.1
The Study
3.5.2
Practice Problem 1.5
3.6
Investigation 1.6: Kissing the Right Way
3.6.1
The Study
3.6.2
Practice Problem 1.6
3.7
Summary of Exact Binomial Inference
4
Normal Approximations for Sample Proportions
4.1
Investigation 1.7: Reese’s Pieces (optional)
4.1.1
Sampling Distributions
4.1.2
Practice Problem 1.7A
4.1.3
Practice Problem 1.7B
4.2
Investigation 1.8: Halloween Treat Choices
4.2.1
The Study
4.2.2
Practice Problem 1.8A
4.2.3
Practice Problem 1.8B
4.3
Summary of One Proportion
z
-test
4.4
Probability Detour: Normal Random Variables
4.5
Investigation 1.9: Kissing the Right Way (cont.)
4.5.1
Interval of plausible values based on Central Limit Theorem
4.5.2
Practice Problem 1.9A
4.5.3
Practice Problem 1.9B
4.6
Investigation 1.10: Heart Transplant Mortality (cont.)
4.6.1
More Confidence Intervals
4.6.2
Practice Problem 1.10A
4.6.3
Practice Problem 1.10B
4.7
Summary: Confidence Interval Methods
4.8
Investigation 1.11: Ganzfeld Experiments
4.8.1
The Study
4.8.2
Practice Problem 1.11A
4.8.3
Practice Problem 1.11B
4.8.4
Practice Problem 1.11C
4.8.5
Practice Problem 1.11D
4.8.6
Practice Problem 1.11E
4.8.7
Practice Problem 1.11F
5
Sampling from a Finite Population
5.1
Activity: Collecting Data
5.2
Investigation 1.12: Sampling Words
5.2.1
Background
5.2.2
Practice Problem 1.12A
5.2.3
Practice Problem 1.12B
5.3
Investigation 1.13: Sampling Words (cont.)
5.3.1
Estimating the Standard Deviation of Sample Proportions
5.3.2
Practice Problem 1.13A
5.3.3
Practice Problem 1.13B
5.4
Investigation 1.14: Teen Hearing Loss
5.4.1
The Study
5.4.2
Practice Problem 1.14
5.5
Summary of One Proportion
\(z\)
-Procedures for Large Population
5.6
Investigation 1.15: Counting Concussions
5.6.1
The Study
5.6.2
Practice Problem 1.15A
5.6.3
Practice Problem 1.15B
5.7
Investigation 1.16: Literary Digest
5.7.1
The Data
5.7.2
Practice Problem 1.16A
5.7.3
Practice Problem 1.16B
5.7.4
Practice Problem 1.16C
5.7.5
Practice Problem 1.16D
5.8
Investigation 1.17: Cat Households
5.8
The Data
5.9
Investigation 1.18: Women Senators
5.9
The Data
6
Chapter 1 Wrap-Up
6.1
Example 1.1: Predicting Elections from Faces?
6.2
Example 1.2: Cola Discrimination
6.3
Example 1.3: Seat Belt Usage
6.1
Chapter 1 Summary
6.2
Summary of What You Have Learned in This Chapter
6.3
Technology Summary
6.4
Quick Reference to ISCAM R Workspace Functions
6.5
Quick Reference to JMP Commands
6.6
Choice of Procedures for Analyzing One Proportion
6.7
Chapter 1 Appendix: Stratified Random Sampling
7
ISCAM
Ch. 2 Intro
8
Descriptive Statistics for Quantitative Data
8.1
Investigation 2.1: Birth Weights
8.1.1
The Data
8.1.2
Practice Problem 2.1A
8.1.3
Practice Problem 2.1B
8.1.4
Practice Problem 2.1C
8.2
Investigation 2.2: Honking Reaction Times
8.2.1
The Study
8.2.2
Practice Problem 2.2A
8.2.3
Practice Problem 2.2B
8.3
Investigation 2.3: Readability of Cancer Pamphlets
8.3.1
The Study
8.3.2
Practice Problem 2.3
9
Inference for a Population Mean
9.1
Investigation 2.4: The Ethan Allen
9.1.1
The Scenario
9.1.2
Practice Problem 2.4A
9.1.3
Practice Problem 2.4B
9.1.4
Practice Problem 2.4C
9.2
Investigation 2.5: What is a healthy body temperature?
9.2.1
The Claim
9.2.2
Practice Problem 2.5A
9.2.3
Practice Problem 2.5B
9.2.4
Practice Problem 2.5C
9.3
Investigation 2.6: Healthy Body Temperatures (cont.)
9.3.1
Estimating the parameter
9.3.2
Practice Problem 2.6A
9.3.3
Practice Problem 2.6B
9.4
Summary of One-sample
\(t\)
Procedures
10
Inference for Other Statistics
10.1
Investigation 2.7: Water Oxygen Levels
10.1.1
The Study
10.1.2
Practice Problem 2.7
10.2
Investigation 2.8: Turbidity
10.2.1
The Study
10.2.2
Practice Problem 2.8
11
Chapter 2 Wrap-Up
11.1
Example 2.1: Pushing On
11.2
Example 2.2: Distracted Driving?
11.1
Chapter 2 Summary
11.2
Summary of What You Have Learned in This Chapter
11.3
Technology Summary
11.4
Quick Reference to ISCAM R Workspace Functions and R Commands
11.5
Quick Reference to JMP Commands
11.6
Choice of Procedures for Analyzing One Mean
12
ISCAM
Ch. 3 Intro
13
Comparing Two Population Proportions
13.1
Investigation 3.1: Teen Hearing Loss (cont.)
13.1.1
The Study
13.1.2
Practice Problem 3.1A
13.1.3
Practice Problem 3.1B
13.2
Summary of Comparing Two Population Proportions
13.3
Investigation 3.2: Nightlights and Near-sightedness
13.3.1
The Study
13.3.2
Practice Problem 3.2A
13.3.3
Practice Problem 3.2B
14
Types of Studies
14.1
Investigation 3.3: Handwriting and SAT Scores
14.1.1
The Study
14.1.2
Practice Problem 3.3
14.2
Investigation 3.4: Botox for Back Pain
14.2.1
The Study
14.2.2
Practice Problem 3.4A
14.2.3
Practice Problem 3.4B
14.2.4
Practice Problem 3.4C
15
Comparing Two Treatment Probabilities
15.1
Investigation 3.5: Dolphin Therapy
15.1.1
The Study
15.1.2
Practice Problem 3.5A
15.1.3
Practice Problem 3.5B
15.2
Investigation 3.6: Is Yawning Contagious?
15.2.1
The Study
15.2.2
Practice Problem 3.6A
15.2.3
Practice Problem 3.6B
15.2.4
Practice Problem 3.6C
15.3
Investigation 3.7: CPR vs. Chest Compressions
15.3.1
The Study
15.3.2
Practice Problem 3.7A
15.3.3
Practice Problem 3.7B
15.4
Investigation 3.8: Peanut Allergies
15.4.1
The Study
15.4.2
Practice Problem 3.8A
15.4.3
Practice Problem 3.8B
15.5
Summary of Inference for Relative Risk
15.6
Investigation 3.9: Smoking and Lung Cancer
15.6.1
The (First!) Study
15.6.2
Practice Problem 3.9A
15.6.3
Practice Problem 3.9B
15.7
Summary of Inference for Odds Ratio
15.8
Investigation 3.10: Sleepy Drivers
15.8.1
The Study
15.8.2
Practice Problem 3.10
16
Chapter 3 Wrap Up
16.1
Example 3.1: Wording of Questions
16.2
Example 3.2: Unbanked Households
16.3
Chapter 3 Summary
16.4
Summary of What You Have Learned in This Chapter
16.5
Technology Summary
16.6
Choice of Procedures for Comparing Two Proportions
16.7
Quick Reference to ISCAM R Workspace Functions and Other R Commands
16.8
Quick Reference to JMP Commands
16.9
Technology Detour – Simulating Random Assignment (two-way tables)
17
ISCAM
Ch. 4 Intro
18
Section 1: Comparing Two Groups with a Quantitative Response
18.1
Investigation 4.1: Employment Discrimination?
18.1.1
The Court Case
18.1.2
Practice Problem 4.1
19
Section 2: Comparing Two Population Means
19.1
Comparing Groups
19.1.1
Investigation 4.2: The Elephants in the Room
19.1.2
Probability Detour: Sampling Distribution of Difference in Two Means
19.1.3
Back to the Elephants
19.1.4
Practice Problem 4.2A
19.1.5
Practice Problem 4.2B
19.1.6
Practice Problem 4.2C
19.2
Investigation 4.3: Left-Handedness and Life Expectancy
19.2.1
The Study
19.2.2
Practice Problem 4.3A
19.2.3
Practice Problem 4.3B
19.3
Applet Exploration
19.3
Guess the p-value
20
Section 3: Comparing Two Treatment Means
20.1
Investigation 4.4: Lingering Effects of Sleep Deprivation
20.1.1
The Study
20.1.2
Practice Problem 4.4A
20.1.3
Practice Problem 4.4B
20.2
Investigation 4.5: Lingering effects of sleep deprivation (cont.)
20.2.1
Two-sample
t
-tests
20.2.2
Practice Problem 4.5
20.3
Investigation 4.6: Ice Cream Serving Sizes
20.3.1
Two-sample
t
-confidence intervals
20.3.2
Practice Problem 4.6
20.4
Investigation 4.7: Cloud Seeding
20.4.1
Strategies for Non-normal Data
20.4.2
Practice Problem 4.7
21
Section 4: Matched Pairs Designs
21.1
Investigation 4.8: Speed It Up
21.1.1
Independent vs. Paired Designs
21.1.2
Practice Problem 4.8A
21.1.3
Practice Problem 4.8B
21.2
Investigation 4.9: Speed It Up (cont.)
21.2.1
Inference for Paired Designs
21.2.2
Practice Problem 4.9A
21.2.3
Practice Problem 4.9B
21.3
Investigation 4.10: Comparison Shopping
21.3.1
Exercises
21.3.2
Practice Problem 4.10A
21.3.3
Practice Problem 4.10B
21.3.4
Practice Problem 4.10C
21.3.5
Practice Problem 4.10D
21.4
Summary of Procedures for Paired Differences
21.5
Investigation 4.11: Smoke Alarms
21.5.1
McNemar’s Test
21.5.2
Practice Problem 4.11
22
Chapter 4 Wrap-Up
22.1
Example 4.1: Age Discrimination?
22.2
Example 4.2: Speed Limit Changes
22.3
Example 4.3: Distracted Driving?
22.4
Example 4.4: Comparison Shopping in the Future
22.5
Chapter 4 Summary
22.5.1
Summary
22.5.2
Summary of What You Have Learned in This Chapter
22.5.3
Technology Summary
22.5.4
Quick Reference to ISCAM Workspace Functions and other R Commands
22.5.5
Quick Reference to JMP Commands
22.5.6
Choice of Procedures for Comparing Two Means
Backmatter
A
Glossary of Terms
B
ISCAM Resources
Index
Colophon
Chapter
14
Types of Studies
In the previous investigation, we cautioned against jumping to a cause-and-effect conclusion when a statistically significant association is found between the response and explanatory variables. But when can we potentially draw such a conclusion?
🔗
14.1
Investigation 3.3: Handwriting and SAT Scores
14.2
Investigation 3.4: Botox for Back Pain
🔗
