Mind on Statistics 5th edition

Textbook Cover

Jessica M. Utts and Robert F. Heckard
Publisher: Cengage Learning

eBook

eBook

Your students can pay an additional fee for access to an online version of the textbook that might contain additional interactive features.

lifetime of edition

Lifetime of Edition (LOE)

Your students are allowed unlimited access to WebAssign courses that use this edition of the textbook at no additional cost.

course pack

Course Packs

Save time with ready-to-use assignments built by subject matter experts specifically for this textbook. You can customize and schedule any of the assignments you want to use.


  • College Success Toolkit
  • Math Mindset
  • Utts and Heckard Mind on Statistics 5e: Stats in Practice Video Questions
  • Utts and Heckard Mind on Statistics 5e: Labs - TI Calculators
  • Utts and Heckard Mind on Statistics 5e: Labs - Excel
  • Utts and Heckard Mind on Statistics 5e: Labs - JMP
  • Utts and Heckard Mind on Statistics 5e: Labs - Minitab
  • Utts and Heckard Mind on Statistics 5e: Labs - SPSS
  • Utts and Heckard Mind on Statistics 5e: Labs - R
  • Utts and Heckard Mind on Statistics 5e: Project Milestones

Access is contingent on use of this textbook in the instructor's classroom.

  • Chapter 1: Statistics Success Stories and Cautionary Tales
    • 1: Concept Explorations
    • 1.1: What Is Statistics?
    • 1.2: Eight Statistical Stories with Morals
    • 1.3: The Common Elements in the Eight Stories
    • 1: Chapter Exercises
    • 1: Extra Problems
    • 1: Active Examples
    • 1: Concept Questions
    • 1: Test Bank

  • Chapter 2: Turning Data into Information
    • 2: Concept Explorations
    • 2: SALT Tutorial - Supporting Sections 2.3, 2.4, 2.5, and 2.6
    • 2.1: Raw Data
    • 2.2: Types of Variables
    • 2.3: Summarizing One or Two Categorical Variables
    • 2.4: Exploring Features of Quantitative Data with Pictures
    • 2.5: Numerical Summaries of Quantitative Variables
    • 2.6: How to Handle Outliers
    • 2.7: Bell-Shaped Distributions and Standard Deviations
    • 2: Chapter Exercises
    • 2: Dataset Exercises
    • 2: Extra Problems
    • 2: Select Your Scenario (beta) - Supporting Sections 2.3, 2.4, 2.5, and 2.6
    • 2: Active Examples
    • 2: JMP Simulations
    • 2: Concept Questions
    • 2: Labs
    • 2: Test Bank

  • Chapter 3: Relationships Between Quantitative Variables
    • 3: Concept Explorations
    • 3: SALT Tutorial
    • 3.1: Looking for Patterns with Scatterplots
    • 3.2: Describing Linear Patterns with a Regression Line
    • 3.3: Measuring Strength and Direction with Correlation
    • 3.4: Regression and Correlation Difficulties and Disasters
    • 3.5: Correlation Does Not Prove Causation
    • 3: Chapter Exercises
    • 3: Dataset Exercises
    • 3: Extra Problems
    • 3: Select Your Scenario (beta)
    • 3: Active Examples
    • 3: JMP Simulations
    • 3: Concept Questions
    • 3: Labs
    • 3: Test Bank

  • Chapter 4: Relationships Between Categorical Variables
    • 4: Concept Explorations
    • 4.1: Displaying Relationships Between Categorical Variables
    • 4.2: Risk, Relative Risk, and Misleading Statistics about Risk
    • 4.3: The Effect of a Third Variable and Simpson's Paradox
    • 4.4: Assessing the Statistical Significance of a 2 × 2 Table
    • 4: Chapter Exercises
    • 4: Dataset Exercises
    • 4: Extra Problems
    • 4: Active Examples
    • 4: JMP Simulations
    • 4: Concept Questions
    • 4: Labs
    • 4: Test Bank

  • Chapter 5: Sampling: Surveys and How to Ask Questions
    • 5: Concept Explorations
    • 5.1: Collecting and Using Sample Data Wisely
    • 5.2: Margin of Error, Confidence Intervals, and Sample Size
    • 5.3: Choosing a Simple Random Sample
    • 5.4: Additional Probability Sampling Methods
    • 5.5: Difficulties and Disasters in Sampling
    • 5.6: Pitfalls in Asking Survey Questions
    • 5: Chapter Exercises
    • 5: Extra Problems
    • 5: Active Examples
    • 5: Concept Questions
    • 5: Labs
    • 5: Test Bank

  • Chapter 6: Gathering Useful Data for Examining Relationships
    • 6: Concept Explorations
    • 6.1: Speaking the Language of Research Studies
    • 6.2: Designing a Good Experiment
    • 6.3: Designing a Good Observational Study
    • 6.4: Difficulties and Disasters in Experiments and Observational Studies
    • 6: Chapter Exercises
    • 6: Extra Problems
    • 6: Active Examples
    • 6: Concept Questions
    • 6: Test Bank

  • Chapter 7: Probability
    • 7: Concept Explorations
    • 7.1: Random Circumstances
    • 7.2: Interpretations of Probability
    • 7.3: Probability Definitions and Relationships
    • 7.4: Basic Rules for Finding Probabilities
    • 7.5: Conditional Probabilities and Bayes' Rule
    • 7.6: Using Simulation to Estimate Probabilities
    • 7.7: Flawed Intuitive Judgments about Probability
    • 7: Chapter Exercises
    • 7: Extra Problems
    • 7: Active Examples
    • 7: Concept Questions
    • 7: Labs
    • 7: Test Bank

  • Chapter 8: Random Variables
    • 8: Concept Explorations
    • 8: SALT Tutorial - Supporting Sections 8.4 and 8.6
    • 8.1: What Is a Random Variable?
    • 8.2: Discrete Random Variables
    • 8.3: Expectations for Random Variables
    • 8.4: Binomial Random Variables
    • 8.5: Continuous Random Variables
    • 8.6: Normal Random Variables
    • 8.7: Approximating Binomial Distribution Probabilities
    • 8.8: Sums, Differences, and Combinations of Random Variables
    • 8: Chapter Exercises
    • 8: Extra Problems
    • 8: Select Your Scenario (beta) - Supporting Sections 8.4 and 8.6
    • 8: Active Examples
    • 8: JMP Simulations
    • 8: Concept Questions
    • 8: Labs
    • 8: Test Bank

  • Chapter 9: Understanding as Sampling Distributions: Statistics as Random Variables
    • 9: Concept Explorations
    • 9.1: Parameters, Statistics, and Statistical Inference
    • 9.2: From Curiosity to Questions About Parameters
    • 9.3: SD Module 0: An Overview of Sampling Distributions
    • 9.4: SD Module 1: Sampling Distribution for One Sample Proportion
    • 9.5: SD Module 2: Sampling Distribution for the Difference in Two Sample Proportions
    • 9.6: SD Module 3: Sampling Distribution for One Sample Mean
    • 9.7: SD Module 4: Sampling Distribution for the Sample Mean of Paired Differences
    • 9.8: SD Module 5: Sampling Distribution for the Difference in Two Sample Means
    • 9.9: Preparing for Statistical Inference: Standardized Statistics
    • 9.10: Generalizations beyond the Big Five
    • 9: Chapter Exercises
    • 9: Dataset Exercises
    • 9: Extra Problems
    • 9: Active Examples
    • 9: Concept Questions
    • 9: Labs
    • 9: Test Bank

  • Chapter 10: Estimating Proportions with Confidence
    • 10: Concept Explorations
    • 10: SALT Tutorial - Supporting Sections 10.1, 10.2, and 10.3
    • 10.1: CI Module 0: An Overview of Confidence Intervals
    • 10.2: CI Module 1: Confidence Intervals for Population Proportions
    • 10.3: CI Module 2: Confidence Intervals for the Difference in Two Population Proportions
    • 10.4: Using Confidence Intervals to Guide Decisions
    • 10: Chapter Exercises
    • 10: Dataset Exercises
    • 10: Extra Problems
    • 10: Select Your Scenario (beta) - Supporting Sections 10.1, 10.2, and 10.3
    • 10: Active Examples
    • 10: JMP Simulations
    • 10: Concept Questions
    • 10: Labs
    • 10: Test Bank

  • Chapter 11: Estimating Means with Confidence
    • 11: Concept Explorations
    • 11: SALT Tutorial - Supporting Sections 11.1, 11.2, and 11.4
    • 11.1: Introduction to Confidence Intervals for Means
    • 11.2: CI Module 3: Confidence Intervals for One Population Mean
    • 11.3: CI Module 4: Confidence Intervals for the Population Mean of Paired Differences
    • 11.4: CI Module 5: Confidence Intervals for the Difference in Two Population Means (Independent Samples)
    • 11.5: Understanding Any Confidence Interval
    • 11: Chapter Exercises
    • 11: Dataset Exercises
    • 11: Extra Problems
    • 11: Select Your Scenario (beta) - Supporting Sections 11.1, 11.2, and 11.4
    • 11: Active Examples
    • 11: JMP Simulations
    • 11: Concept Questions
    • 11: Labs
    • 11: Test Bank

  • Chapter 12: Testing Hypotheses about Proportions
    • 12: Concept Explorations
    • 12: SALT Tutorial - Supporting Sections 12.2 and 12.3
    • 12.1: HT Module 0: An Overview of Hypothesis Testing
    • 12.2: HT Module 1: Testing Hypotheses about a Population Proportion
    • 12.3: HT Module 2: Testing Hypotheses about the Difference in Two Population Proportions
    • 12.4: Sample Size, Statistical Significance, and Practical Importance
    • 12: Chapter Exercises
    • 12: Dataset Exercises
    • 12: Extra Problems
    • 12: Select Your Scenario (beta) - Supporting Sections 12.2 and 12.3
    • 12: Active Examples
    • 12: JMP Simulations
    • 12: Concept Questions
    • 12: Labs
    • 12: Test Bank

  • Chapter 13: Testing Hypotheses about Means
    • 13: Concept Explorations
    • 13: SALT Tutorial - Supporting Sections 13.2, 13.3, and 13.4
    • 13.1: Introduction to Hypothesis Tests for Means
    • 13.2: HT Module 3: Testing Hypotheses about One Population Mean
    • 13.3: HT Module 4: Testing Hypotheses about the Population Mean of Paired Differences
    • 13.4: HT Module 5: Testing Hypotheses about the Difference in Two Population Means (Independent Samples)
    • 13.5: The Relationship Between Significance Tests and Confidence Intervals
    • 13.6: Choosing an Appropriate Inference Procedure
    • 13.7: Effect Size
    • 13.8: Evaluating Significance in Research Reports
    • 13: Chapter Exercises
    • 13: Dataset Exercises
    • 13: Extra Problems
    • 13: Select Your Scenario (beta) - Supporting Sections 13.2, 13.3, and 13.4
    • 13: Active Examples
    • 13: JMP Simulations
    • 13: Concept Questions
    • 13: Labs
    • 13: Test Bank

  • Chapter 14: Inference about Simple Regression
    • 14: Concept Explorations
    • 14: SALT Tutorial
    • 14.1: Sample and Population Regression Models
    • 14.2: Estimating the Standard Deviation for Regression
    • 14.3: Inference about the Slope of a Linear Regression
    • 14.4: Predicting y and Estimating Mean y at a Specific x
    • 14.5: Checking Conditions for Using Regression Models for Inference
    • 14: Chapter Exercises
    • 14: Dataset Exercises
    • 14: Extra Problems
    • 14: Select Your Scenario (beta)
    • 14: Active Examples
    • 14: JMP Simulations
    • 14: Concept Questions
    • 14: Labs
    • 14: Test Bank

  • Chapter 15: More about Inference for Categorical Variables
    • 15: Concept Explorations
    • 15.1: The Chi-Square Test for Two-Way Tables
    • 15.2: Methods for Analyzing 2 × 2 Tables
    • 15.3: Testing Hypotheses about One Categorical Variable: Goodness-of-Fit
    • 15: Chapter Exercises
    • 15: Dataset Exercises
    • 15: Extra Problems
    • 15: Active Examples
    • 15: JMP Simulations
    • 15: Concept Questions
    • 15: Labs
    • 15: Test Bank

  • Chapter 16: Analysis of Variance
    • 16: Concept Explorations
    • 16.1: Comparing Means with an ANOVA F-Test
    • 16.2: Details of One-Way Analysis of Variance
    • 16.3: Other Methods for Comparing Populations
    • 16.4: Two-Way Analysis of Variance
    • 16: Chapter Exercises
    • 16: Dataset Exercises
    • 16: Extra Problems
    • 16: Active Examples
    • 16: JMP Simulations
    • 16: Concept Questions
    • 16: Labs
    • 16: Test Bank

  • Chapter 17: Turning Information into Wisdom
    • 17: Concept Explorations
    • 17.1: Beyond the Data
    • 17.2: Transforming Uncertainty Into Wisdom
    • 17.3: Making Personal Decisions
    • 17.4: Control of Societal Risks
    • 17.5: Understanding Our World
    • 17.6: Getting to Know You
    • 17.7: Words to the Wise
    • 17: Chapter Exercises
    • 17: Extra Problems
    • 17: Active Examples
    • 17: Concept Questions

  • Chapter S1: Additional Discrete Random Variables
    • S1.1: Hypergeometric Distribution
    • S1.2: Poisson Distribution
    • S1.3: Multinomial Distribution

  • Chapter S2: Nonparametric Tests of Hypotheses
    • S2: Concept Explorations
    • S2.1: Sign Test
    • S2.2: The Two-Sample Rank Sum Test
    • S2.3: Wilcoxon Signed-Rank Test
    • S2.4: Kruskal-Wallis Test

  • Chapter S3: Multiple Regression
    • S3: Concept Explorations
    • S3.1: The Multiple Linear Regression Model
    • S3.2: Inference for Multiple Regression Models
    • S3.3: Checking Conditions for Multiple Linear Regression

  • Chapter S4: Two-Way Analysis of Variance
    • S4.1: Assumptions and Models for Two-Way ANOVA
    • S4.2: Testing for Main Effects and Interactions

  • Chapter S5: Ethics
    • S5.1: Ethical Treatment of Human and Animal Participants
    • S5.2: Assurance of Data Quality
    • S5.3: Appropriate Statistical Analyses
    • S5.4: Fair Reporting of Results

  • Chapter PJT: Project
    • PJT.1: Project

Questions Available within WebAssign

Most questions from this textbook are available in WebAssign. The online questions are identical to the textbook questions except for minor wording changes necessary for Web use. Whenever possible, variables, numbers, or words have been randomized so that each student receives a unique version of the question. This list is updated nightly.

Question Availability Color Key
BLACK questions are available now
GRAY questions are under development


Group Quantity Questions
Chapter 1: Statistics Success Stories and Cautionary Tales
1 0  
Chapter 2: Turning Data into Information
2 0  
Chapter 3: Relationships Between Quantitative Variables
3 0  
Chapter 4: Relationships Between Categorical Variables
4 0  
Chapter 5: Sampling: Surveys and How to Ask Questions
5 0  
Chapter 6: Gathering Useful Data for Examining Relationships
6 0  
Chapter 7: Probability
7 0  
Chapter 8: Random Variables
8 0  
Chapter 9: Understanding as Sampling Distributions: Statistics as Random Variables
9 0  
Chapter 10: Estimating Proportions with Confidence
10 0  
Chapter 11: Estimating Means with Confidence
11 0  
Chapter 12: Testing Hypotheses about Proportions
12 0  
Chapter 13: Testing Hypotheses about Means
13 0  
Chapter 14: Inference about Simple Regression
14 0  
Chapter 15: More about Inference for Categorical Variables
15 0  
Chapter 16: Analysis of Variance
16 0  
Chapter 17: Turning Information into Wisdom
17 0  
Total 0