Interactive Statistics: Informed Decisions Using Data, Global Edition, 3rd edition

Published by Pearson (April 7, 2025) © 2025

  • Michael Sullivan Chicago State University
  • George Woodbury College of the Sequoias
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Title overview

Interactive Statistics: Informed Decisions Using Data encourages you to do statistics actively as you learn, experiencing statistics in new and dynamic ways as you encounter concepts. Written fully in MyLab® Statistics, it combines text, multimedia and assessment into a seamless learning experience. Interactive Assignments for each chapter section prompt you to “read a little, watch a little, do a little” to develop deeper conceptual connections. This practical approach in an interactive, guided learning environment promotes deeper understanding, knowledge retention and ability to connect statistics to the world at large. The 3rd Edition updates and adds content throughout to content, data, and the MyLab platform.

Table of contents

1: Data Collection

  • 1.1 Introduction to the Practice of Statistics
  • 1.2 Observational Studies versus Designed Experiments
  • 1.3 Simple Random Sampling
  • 1.4 Other Effective Sampling Methods
  • 1.5 Bias in Sampling
  • 1.6 The Design of Experiments
  • Chapter 1 Review
  • Chapter 1 Practice Test
  • Chapter 1 Projects

2: Organizing and Summarizing Data

  • Preparing for Section 2.1: Organizing Qualitative Data
  • 2.1 Organizing Qualitative Data
  • Preparing for Section 2.2: Organizing Quantitative Data: The Popular Displays
  • 2.2 Organizing Quantitative Data: The Popular Displays
  • 2.3 Additional Displays of Quantitative Data
  • 2.4 Graphical Misrepresentations of Data
  • Chapter 2 Review
  • Chapter 2 Practice Test
  • Chapter 2 Projects

3: Numerically Summarizing Data

  • Preparing for Section 3.1: Measures of Central Tendency
  • 3.1 Measures of Central Tendency
  • 3.2 Measures of Dispersion
  • Preparing for Section 3.3: Measures of Central Tendency and Dispersion from Grouped Data
  • 3.3 Measures of Central Tendency and Dispersion from Grouped Data
  • 3.4 Measures of Position
  • 3.5 The Five-Number Summary and Boxplots
  • Chapter 3 Review
  • Chapter 3 Practice Test
  • Chapter 3 Projects

4: Describing the Relation between Two Variables

  • Preparing for Section 4.1: Scatter Diagrams and Correlation
  • 4.1 Scatter Diagrams and Correlation
  • Preparing for Section 4.2: Least-Squares Regression
  • 4.2 Least-Squares Regression
  • Preparing for Section 4.3: Diagnostics on the Least-Squares Regression Line
  • 4.3 Diagnostics on the Least-Squares Regression Line
  • Preparing for Section 4.4: Contingency Tables and Association
  • 4.4 Contingency Tables and Association
  • Chapter 4 Review
  • Chapter 4 Practice Test
  • Chapter 4 Projects

5: Probability

  • Preparing for Section 5.1: Probability Rules
  • 5.1 Probability Rules
  • 5.2 The Addition Rule and Complements
  • 5.3 Independence and the Multiplication Rule
  • 5.4 Conditional Probability and the General Multiplication Rule
  • 5.5 Counting Techniques
  • 5.6 Simulation
  • 5.7 Putting It Together: Which Method Do I Use?
  • Chapter 5 Review
  • Chapter 5 Practice Test
  • Chapter 5 Projects

6: Discrete Probability Distributions

  • Preparing for Section 6.1: Discrete Random Variables
  • 6.1 Discrete Random Variables
  • Preparing for Section 6.2: The Binomial Probability Distribution
  • 6.2 The Binomial Probability Distribution
  • 6.3 The Poisson Probability Distribution
  • Chapter 6 Review
  • Chapter 6 Practice Test
  • Chapter 6 Projects

7: The Normal Probability Distribution

  • Preparing for Section 7.1: Properties of the Normal Distribution
  • 7.1 Properties of the Normal Distribution
  • Preparing for Section 7.2: Applications of the Normal Distribution
  • 7.2 Applications of the Normal Distribution
  • Preparing for Section 7.3: Assessing Normality
  • 7.3 Assessing Normality
  • Preparing for Section 7.4: The Normal Approximation to the Binomial Probability Distribution
  • 7.4 The Normal Approximation to the Binomial Probability Distribution
  • Chapter 7 Review
  • Chapter 7 Practice Test
  • Chapter 7 Projects

8: Sampling Distributions

  • Preparing for Section 8.1: Distribution of the Sample Mean
  • 8.1 Distribution of the Sample Mean
  • Preparing for Section 8.2: Distribution of the Sample Proportion
  • 8.2 Distribution of the Sample Proportion
  • Chapter 8 Review
  • Chapter 8 Practice Test
  • Chapter 8 Projects

9: Estimating the Value of a Parameter

  • Preparing for Section 9.1: Estimating a Population Proportion
  • 9.1 Estimating a Population Proportion
  • Preparing for Section 9.2: Estimating a Population Mean
  • 9.2 Estimating a Population Mean
  • 9.3 Putting It Together: Which Procedure Do I Use?
  • 9.4 Estimating with Bootstrapping
  • Chapter 9 Review
  • Chapter 9 Practice Test
  • Chapter 9 Projects

10: Hypothesis Tests Regarding a Parameter

  • Preparing for Section 10.1: Estimating a Population Mean
  • 10.1 The Language of Hypothesis Testing
  • Preparing for Section 10.2 Hypothesis Tests for a Population Proportion
  • 10.2 Hypothesis Tests for a Population Proportion
  • Preparing for Section 10.3 Hypothesis Tests for a Population Mean
  • 10.3 Hypothesis Tests for a Population Mean
  • Preparing for Section 10.3A Hypothesis Tests on a Population Mean Using Simulation and the Bootstrap
  • 10.3A Hypothesis Tests on a Population Mean Using Simulation and the Bootstrap
  • Chapter 10 Review
  • Chapter 10 Practice Test
  • Chapter 10 Projects

11: Inference on Two Samples

  • Preparing for Section 11.1: Inference about Two Population Proportions
  • 11.1 Inference about Two Population Proportions: Independent Samples
  • 11.1A Using Randomization Techniques to Compare Two Proportions
  • Preparing for Section 11.2: Inference about Two Population Means: Dependent Samples
  • 11.2 Inference about Two Population Means: Dependent Samples
  • Preparing for Section 11.2A: Using Bootstrapping to Conduct Inference on Two Dependent Means
  • 11.2A Using Bootstrapping to Conduct Inference on Two Dependent Means
  • Preparing for Section 11.3: Inference about Two Population Means: Independent Samples
  • 11.3 Inference about Two Population Means: Independent Samples
  • 11.3A Using Randomization Techniques to Compare Two Independent Means
  • 11.4 Putting It Together: Which Procedure Do I Use?
  • Chapter 11 Review
  • Chapter 11 Practice Test
  • Chapter 11 Projects

12: Inference on Categorical Data

  • Preparing for Section 12.1: Goodness-of-Fit Test
  • 12.1 Goodness-of-Fit Test
  • Preparing for Section 12.2: Tests for Independence and the Homogeneity of Proportions
  • 12.2 Tests for Independence and the Homogeneity of Proportions
  • Preparing for Section 12.3: Inference about Two Population Proportions: Dependent Samples
  • 12.3 Inference about Two Population Proportions: Dependent Samples
  • Chapter 12 Review
  • Chapter 12 Practice Test
  • Chapter 12 Projects

13: Comparing Three or More Means

  • Preparing for Section 13.1: Comparing Three or More Means: One-Way Analysis of Variance
  • 13.1 Comparing Three or More Means: One-Way Analysis of Variance
  • Preparing for Section 13.2: Post Hoc Tests on One-Way Analysis of Variance
  • 13.2 Post Hoc Tests on One-Way Analysis of Variance
  • Chapter 13 Review
  • Chapter 13 Practice Test
  • Chapter 13 Projects

14: Inference on the Least-Squares Regression Model and Multiple Regression

  • Preparing for Section 14.1: Testing the Significance of the Least-Squares Regression Model
  • 14.1 Testing the Significance of the Least-Squares Regression Model
  • 14.1A Using Randomization Techniques on the Slope of the Least-Squares Regression Line
  • Preparing for Section 14.2: Confidence and Prediction Intervals
  • 14.2 Confidence and Prediction Intervals
  • Preparing for Section 14.3: Introduction to Multiple Regression
  • Chapter 14 Review
  • Chapter 14 Practice Test
  • Chapter 14 Projects
Appendix

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