1.1 Preliminary: Introduction to the six-step method
1.2 Preliminary: Exploring data
1.3 Preliminary: Exploring random processes

2.1 Example: Introduction to chance models
2.2 Example: Measuring the strength of evidence
2.3 Example: Alternative measure of strength of evidence
2.4 Example: What impacts strength of evidence?
2.5 Example: Inference on a single proportion: Theory-based approach
2.6 Exploration: Introduction to chance models
2.7 Exploration: Measuring the strength of evidence
2.8 Exploration: Alternative measure of strength of evidence
2.9 Exploration: What impacts strength of evidence?
2.10 Exploration: Inference on a single proportion: Theory-based approach
2.11 Investigation: Tire story falls flat

3.1 Example: Sampling from a finite population
3.2 Example: Inference for a single quantitative variable
3.3 Example: Theory-based Inference for a Population Mean
3.4 Example: Other statistics
3.5 Exploration: Sampling from a finite population
3.6 Exploration: Inference for a single quantitative variable
3.7 Exploration: Theory-based Inference for a Population Mean
3.8 Exploration: Other statistics
3.9 Investigation: Faking cell phone calls

4.1 Example: Statistical inference – confidence intervals
4.2 Example: 2SD and theory-based confidence intervals for a single proportion
4.3 Example: 2SD and theory-based confidence intervals for a single mean
4.4 Example: Factors that affect the width of a confidence interval
4.5 Exploration: Statistical inference – confidence intervals
4.6 Exploration: 2SD and theory-based confidence intervals for a single proportion
4.7 Exploration: 2SD and theory-based confidence intervals for a single mean
4.8 Exploration A: Factors that affect the width of a confidence interval
4.9 Exploration B: Factors that affect the width of a confidence interval
4.10 Investigation: Cell phones while driving

5.1 Example: Association and confounding
5.2 Example: Observational studies vs. experiments
5.3 Exploration: Association and confounding
5.4 Exploration: Observational studies versus experiments
5.5 Investigation: High anxiety and sexual attraction

6.1 Example: Comparing two groups: Categorical response
6.2 Example: Comparing two proportions: Simulation-based approach
6.3 Example: Comparing two proportions: Theory-based approach

7.1 Example: Comparing two groups: Quantitative response
7.2 Example: Comparing two means: Simulation-based approach
7.3 Example: Comparing two means: Theory-based approach

8.1 Example: Paired designs
8.2 Example: Simulation-based approach for analyzing paired data
8.3 Example: Theory-based approach to analyzing data from paired samples

9.1 Example: Comparing multiple proportions: Simulation-based approach
9.2 Example: Comparing multiple proportions: Theory-based approach
9.3 Example: Chi-square goodness-of-fit test

10.1 Example: Comparing multiple means: Simulation-based approach
10.2 Example: Comparing multiple means: Theory-based approach

11.1 Example: Two quantitative variables: Scatterplot and correlation
11.2 Example: Inference for correlation coefficient: A simulation-based approach
11.3 Example: Least squares regression
11.4 Example: Inference for regression slope: Simulation-based approach
11.5 Example: Inference for regression slope: Theory-based approach

## What You’ll Find In This zyBook:

### More action with less text.

Bring the second edition of Tintle/Chance Introduction to Statistical Investigations to life through zyBooks’ interactive learning platform.

• Participation activities immerse students in the process of doing statistics: guided animations, simulation tools, and learning questions with answer-specific feedback
• Auto-graded Challenge Activities provide higher stakes evaluations
• Test Bank extends assessment opportunities
• Tintle’s six-step statistical exploration and investigation method is enhanced and reinforced through zyBooks’ interactive tools
• Optional chapter on probability included
• Designed with flexibility for on-campus, hybrid or fully online courses ## The zyBooks Approach

### Less text doesn’t mean less learning.

Built from the ground up using zyBooks’ pedagogy and in close collaboration with the authors, the Introduction to Statistical Investigations zyBook takes the authors’ spiral approach to the statistical process into a new experiential paradigm. Rather than passively reading along as the authors apply their approach to worked examples, students interact with zyBooks’ guided animations, simulation tools, and learning questions with answer-specific feedback.

By manipulating real-world data and drawing conclusions through these interactive tools, students become immersed in the process of “doing statistics,” which builds confidence and empowers success.

“Best Monty Hall simulation I have ever seen.”