Skip to main content
ISCAM: Investigating Statistical Concepts, Applications, and Methods
Beth L. Chance, Allan J. Rossman
Contents
Index
Search Book
Search Results:
No results.
Calculator
Read aloud
Continue
Read aloud settings
Voice
Reading speed
1×
Collapsed content
Announce, do not read
Read automatically
Follow along (auto-scroll)
Continue to the next page automatically
Readability settings
Readability settings
Line height
1.35
Content font size
100%
Theme
System
Light
Dark
Assistive technologies
🔗
Expose permalinks
Reset All
Prev
Up
Next
Scratch ActiveCode
Profile
title here
\( \newcommand{\lt}{<} \newcommand{\gt}{>} \newcommand{\amp}{&} \definecolor{fillinmathshade}{gray}{0.9} \newcommand{\fillinmath}[1]{\mathchoice{\colorbox{fillinmathshade}{$\displaystyle \phantom{\,#1\,}$}}{\colorbox{fillinmathshade}{$\textstyle \phantom{\,#1\,}$}}{\colorbox{fillinmathshade}{$\scriptstyle \phantom{\,#1\,}$}}{\colorbox{fillinmathshade}{$\scriptscriptstyle\phantom{\,#1\,}$}}} \)
Front Matter
To the Student
Using Technology with This Book
1
Preliminaries
Introduction
1.1
Investigation A: Distributions and Variability
1.1.1
Investigation A: Hurricanes and Climate Change
1.1.2
Practice Problem A.A
1.2
Investigation B: 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
Investigation C: 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
Section 1.1: Analyzing a Process Probability
Introduction
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
Section 1.2: Normal Approximations for Sample Proportions
Introduction
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
Section 1.3: Sampling from a Finite Population
Introduction
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
Introduction
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
Section 2.1: Descriptive Statistics for Quantitative Data
Introduction
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: How Long Can You Stand It?
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
Section 2.2: Inference for a Population Mean
Introduction
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
Section 2.3: Inference for Other Statistics
Introduction
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
10.3
Investigation 2.9: Heroin Treatment Times
10.3.1
The Study
10.3.2
Practice Problem 2.9A
10.3.3
Practice Problem 2.9B
11
Chapter 2 Wrap-Up
Introduction
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
Section 3.1: Comparing Two Population Proportions
Introduction
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
Section 3.2: Types of Studies
Introduction
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
Section 3.3: Comparing Two Treatment Probabilities
Introduction
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
16
Section 3.4: Other Statistics
Introduction
16.1
Investigation 3.8: Peanut Allergies
16.1.1
The Study
16.1.2
Practice Problem 3.8A
16.1.3
Practice Problem 3.8B
16.2
Summary of Inference for Relative Risk
16.3
Investigation 3.9: Smoking and Lung Cancer
16.3.1
The (First!) Study
16.3.2
Practice Problem 3.9A
16.3.3
Practice Problem 3.9B
16.4
Summary of Inference for Odds Ratio
16.5
Investigation 3.10: Sleepy Drivers
16.5.1
The Study
16.5.2
Practice Problem 3.10
17
Chapter 3 Wrap Up
Introduction
17.1
Example 3.1: Wording of Questions
17.2
Example 3.2: Unbanked Households
17.1
Chapter 3 Summary
17.2
Summary of What You Have Learned in This Chapter
17.3
Technology Summary
17.4
Choice of Procedures for Comparing Two Proportions
17.5
Quick Reference to ISCAM R Workspace Functions and Other R Commands
17.6
Quick Reference to JMP Commands
17.3
Technology Detour – Simulating Random Assignment (two-way tables)
18
ISCAM
Ch. 4 Intro
19
Section 4.1: Comparing Two Groups with a Quantitative Response
Introduction
19.1
Investigation 4.1: Employment Discrimination?
19.1.1
The Court Case
19.1.2
Practice Problem 4.1
20
Section 4.2: Comparing Two Population Means
Introduction
20.1
Investigation 4.2: The Elephants in the Room
20.1.1
The Study
20.1.2
Probability Exploration: Simulation of Distribution of Difference in Sample Means
20.1.3
Back to the Elephants
20.1.4
Practice Problem 4.2A
20.1.5
Practice Problem 4.2B
20.1.6
Practice Problem 4.2C
20.2
Investigation 4.3: Left-Handedness and Life Expectancy
20.2.1
The Study
20.2.2
Practice Problem 4.3A
20.2.3
Practice Problem 4.3B
20.3
Applet Exploration
20.3
Guess the p-value
21
Section 4.3: Comparing Two Treatment Means
Introduction
21.1
Investigation 4.4: Lingering Effects of Sleep Deprivation
21.1.1
The Study
21.1.2
Practice Problem 4.4A
21.1.3
Practice Problem 4.4B
21.2
Investigation 4.5: Lingering effects of sleep deprivation (cont.)
21.2.1
Two-sample
t
-tests
21.2.2
Practice Problem 4.5
21.3
Investigation 4.6: Ice Cream Serving Sizes
21.3.1
Two-sample
t
-confidence intervals
21.3.2
Practice Problem 4.6
21.4
Investigation 4.7: Cloud Seeding
21.4.1
Strategies for Non-normal Data
21.4.2
Practice Problem 4.7
22
Section 4.4: Matched Pairs Designs
Introduction
22.1
Investigation 4.8: Speed It Up
22.1.1
Independent vs. Paired Designs
22.1.2
Practice Problem 4.8A
22.1.3
Practice Problem 4.8B
22.2
Investigation 4.9: Speed It Up (cont.)
22.2.1
Inference for Paired Designs
22.2.2
Practice Problem 4.9A
22.2.3
Practice Problem 4.9B
22.3
Investigation 4.10: Comparison Shopping
22.3.1
Exercises
22.3.2
Practice Problem 4.10A
22.3.3
Practice Problem 4.10B
22.3.4
Practice Problem 4.10C
22.3.5
Practice Problem 4.10D
22.4
Summary of Procedures for Paired Differences
22.5
Investigation 4.11: Smoke Alarms
22.5.1
McNemar’s Test
22.5.2
Practice Problem 4.11
23
Chapter 4 Wrap-Up
Introduction
23.1
Example 4.1: Age Discrimination?
23.2
Example 4.2: Speed Limit Changes
23.3
Example 4.3: Distracted Driving?
23.4
Example 4.4: Comparison Shopping in the Future
23.5
Chapter 4 Summary
23.5.1
Summary of What You Have Learned in This Chapter
23.5.2
Technology Summary
23.5.3
Quick Reference to ISCAM Workspace Functions and other R Commands
23.5.4
Quick Reference to JMP Commands
23.5.5
Choice of Procedures for Comparing Two Means
24
ISCAM
Chapter 5 Intro
25
Section 5.1: Two Categorical Variables
Introduction
25.1
Investigation 5.1: Dr. Spock’s Trial
25.1.1
The Study
25.1.2
Practice Problem 5.1
25.2
Investigation 5.1A: Newspaper Credibility Decline
25.2.1
The Study
25.2.2
Practice Problem 5.1A
25.3
Investigation 5.2: Teaching Morals
25.3.1
The Study
25.3.2
Practice Problem 5.2
25.4
Investigation 5.3: Near-Sightedness and Night Lights (cont.)
25.4.1
The Study
25.4.2
Practice Problem 5.3
25.5
Summary of Chi-squared Tests
25.6
Section 5.1 Summary
26
Section 5.2: Comparing Several Population Means
Introduction
26.1
Investigation 5.4: Disability Discrimination
26.1.1
The Study
26.1.2
Practice Problem 5.4A
26.1.3
Practice Problem 5.4B
26.2
Investigation 5.5: Restaurant Spending and Music
26.2.1
The Study
26.2.2
Practice Problem 5.5A
26.2.3
Practice Problem 5.5B
26.3
Applet Exploration: Exploring ANOVA
26.3
Applet Exploration
26.4
Section 5.2 Summary
27
Section 5.3: Relationships Between Quantitative Variables
Introduction
27.1
Investigation 5.6: Cat Jumping
27.1.1
The Study
27.1.2
Practice Problem 5.6
27.2
Investigation 5.7: Drive for Show, Putt for Dough
27.2.1
The Study
27.2.2
Practice Problem 5.7A
27.2.3
Practice Problem 5.7B
27.3
Applet Exploration: Correlation Guessing Game
27.3
Exploration Tasks
27.4
Investigation 5.8: Height and Foot Size
27.4.1
The Study
27.4.2
Practice Problem 5.8
27.5
Applet Exploration: Behavior of Regression Lines
27.5
Exploration Tasks
27.6
Excel Exploration: Minimization Criteria
27.6
Exploration Tasks
27.7
Investigation 5.9: Money-Making Movies
27.7.1
The Study
27.7.2
Practice Problem 5.9A
27.7.3
Practice Problem 5.9B
27.8
Section 5.3 Summary
28
Section 5.4: Inference for Regression
Introduction
28.1
Investigation 5.10: Running Out of Time
28.1.1
The Data
28.1.2
Practice Problem 5.10A
28.1.3
Practice Problem 5.10B
28.2
Investigation 5.11: Running Out of Time (cont.)
28.2.1
The Data Cont.
28.2.2
Practice Problem 5.11
28.3
Investigation 5.12: Boys’ Heights
28.3
The (Hypothetical) Data
28.4
Investigation 5.13: Cat Jumping (cont.)
28.4.1
The Study
28.4.2
Practice Problem 5.13
28.5
Investigation 5.14: Housing Prices
28.5.1
The Study
28.5.2
Practice Problem 5.14
28.6
Summary of Inference for Regression
28.7
Technology Exploration: The Regression Effect
28.7
The Study
28.8
Section 5.4 Summary
29
Chapter 5 Wrap-Up
Introduction
29.1
Example 5.1: Internet Use by Region
29.2
Example 5.2: Lifetimes of Notables
29.3
Example 5.3: Physical Education Class Performance
29.4
Example 5.4: Comparing Popular Diets
29.5
Chapter 5 Summary
29.5.1
Technology Summary
29.5.2
Choice of Procedures for Comparing Several Populations, Exploring Relationships
29.5.3
Quick Reference to ISCAM R Workspace Functions and Other R Commands
29.5.4
Quick Reference to JMP Commands
Backmatter
A.
Glossary of Terms
B.
ISCAM Resources
Index
Colophon
Introduction
In this section, you will begin to analyze results from statistical studies and focus on the process of statistical inference. In particular, you will learn how to assess evidence against a particular claim about a random process.
🔗
