Introduction to Statistics and Data Analysis 6th edition

Textbook Cover

Roxy Peck, Tom Short, and Chris Olsen
Publisher: Cengage Learning

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.


  • Peck Introduction to Statistics and Data Analysis 6e with SALT - Updated July 2021

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

  • Chapter 1: The Role of Statistics and the Data Analysis Process
    • 1: Concept Explorations
    • 1.1: Why Study Statistics?
    • 1.2: The Nature and Role of Variability
    • 1.3: Statistics and the Data Analysis Process
    • 1.4: Types of Data and Some Simple Graphical Displays
    • 1: Chapter Review
    • 1: Active Examples
    • 1: Extra Problems
    • 1: JMP Simulations
    • 1: Concept Questions
    • 1: Test Bank
    • 1: Concept Questions
    • 1: Test Bank

  • Chapter 2: Collecting Data Sensibly
    • 2: Concept Explorations
    • 2.1: Statistical Studies: Observation and Experimentation
    • 2.2: Sampling
    • 2.3: Simple Comparative Experiments
    • 2.4: More on Experimental Design
    • 2.5: Interpreting and Communicating the Results of Statistical Analyses
    • 2: Chapter Review
    • 2: Online Exercises
    • 2: Active Examples
    • 2: Extra Problems
    • 2: Concept Questions
    • 2: Labs
    • 2: Test Bank

  • Chapter 3: Graphical Methods for Describing Data
    • 3: Concept Explorations
    • 3.1: Displaying Categorical Data: Comparative Bar Charts and Pie Charts
    • 3.2: Displaying Numerical Data: Stem-and-Leaf Displays
    • 3.3: Displaying Numerical Data: Frequency Distributions and Histograms
    • 3.4: Displaying Bivariate Numerical Data
    • 3.5: Interpreting and Communicating the Results of Statistical Analyses
    • 3: Chapter Review
    • 3: Active Examples
    • 3: Cumulative Review Exercises
    • 3: Extra Problems
    • 3: JMP Simulations
    • 3: Concept Questions
    • 3: Labs
    • 3: Test Bank
    • 3: Labs
    • 3: Test Bank

  • Chapter 4: Numerical Methods for Describing Data
    • 4: Concept Explorations
    • 4.1: Describing the Center of a Data Set
    • 4.2: Describing Variability in a Data Set
    • 4.3: Summarizing a Data Set: Boxplots
    • 4.4: Interpreting Center and Variability: Chebyshev's Rule, the Empirical Rule, and z Scores
    • 4.5: Interpreting and Communicating the Results of Statistical Analyses
    • 4: Chapter Review
    • 4: Active Examples
    • 4: Extra Problems
    • 4: JMP Simulations
    • 4: Concept Questions
    • 4: Labs
    • 4: Test Bank
    • 4: Labs
    • 4: Test Bank

  • Chapter 5: Summarizing Bivariate Data
    • 5: Concept Explorations
    • 5.1: Correlation
    • 5.2: Linear Regression: Fitting a Line to Bivariate Data
    • 5.3: Assessing the Fit of a Line
    • 5.4: Nonlinear Relationships and Transformations
    • 5.5: Interpreting and Communicating the Results of Statistical Analyses
    • 5: Chapter Review
    • 5: Online Exercises
    • 5: Active Examples
    • 5: Cumulative Review Exercises
    • 5: Extra Problems
    • 5: JMP Simulations
    • 5: Concept Questions
    • 5: Labs
    • 5: Test Bank
    • 5: Labs
    • 5: Test Bank

  • Chapter 6: Probability
    • 6: Concept Explorations
    • 6.1: Chance Experiments and Events
    • 6.2: Definition of Probability
    • 6.3: Basic Properties of Probability
    • 6.4: Conditional Probability
    • 6.5: Independence
    • 6.6: Some General Probability Rules
    • 6.7: Estimating Probabilities Empirically and Using Simulation
    • 6: Chapter Review
    • 6: Active Examples
    • 6: Extra Problems
    • 6: Concept Questions
    • 6: Labs
    • 6: Test Bank

  • Chapter 7: Random Variables and Probability Distributions
    • 7: Concept Explorations
    • 7.1: Random Variables
    • 7.2: Probability Distributions for Discrete Random Variables
    • 7.3: Probability Distributions for Continuous Random Variables
    • 7.4: Mean and Standard Deviation of a Random Variable
    • 7.5: Binomial and Geometric Distributions
    • 7.6: Normal Distributions
    • 7.7: Checking for Normality and Normalizing Transformations
    • 7.8: Using the Normal Distribution to Approximate a Discrete Distribution (Optional)
    • 7: Chapter Review
    • 7: Active Examples
    • 7: Cumulative Review Exercises
    • 7: Extra Problems
    • 7: JMP Simulations
    • 7: Concept Questions
    • 7: Labs
    • 7: Test Bank
    • 7: Labs
    • 7: Test Bank

  • Chapter 8: Sampling Variability and Sampling Distributions
    • 8: Concept Explorations
    • 8.1: Statistics and Sampling Variability
    • 8.2: The Sampling Distribution of a Sample Mean
    • 8.3: The Sampling Distribution of a Sample Proportion
    • 8: Chapter Review
    • 8: Active Examples
    • 8: Extra Problems
    • 8: Concept Questions
    • 8: Labs
    • 8: Test Bank

  • Chapter 9: Estimation Using a Single Sample
    • 9: Concept Explorations
    • 9.1: Point Estimation
    • 9.2: Large-Sample Confidence Interval for a Population Proportion
    • 9.3: Confidence Interval for a Population Mean
    • 9.4: Interpreting and Communicating the Results of Statistical Analyses
    • 9.5: Bootstrap Confidence Intervals for a Population Proportion (Optional)
    • 9.6: Bootstrap Confidence Intervals for a Population Mean (Optional)
    • 9: Chapter Review
    • 9: Active Examples
    • 9: Extra Problems
    • 9: JMP Simulations
    • 9: Concept Questions
    • 9: Labs
    • 9: Test Bank
    • 9: Labs
    • 9: Test Bank

  • Chapter 10: Hypothesis Testing Using a Single Sample
    • 10: Concept Explorations
    • 10.1: Hypotheses and Test Procedures
    • 10.2: Errors in Hypotheses Testing
    • 10.3: Large-Sample Hypothesis Tests for a Population Proportion
    • 10.4: Hypothesis Tests for a Population Mean
    • 10.5: Power and Probability of Type II Error
    • 10.6: Interpreting and Communicating the Results of Statistical Analyses
    • 10.7: Randomization Test and Exact Binomial Test for a Population Proportion (Optional)
    • 10.8: Randomization Test for a Population Mean (Optional)
    • 10: Chapter Review
    • 10: Active Examples
    • 10: Cumulative Review Exercises
    • 10: Extra Problems
    • 10: JMP Simulations
    • 10: Concept Questions
    • 10: Labs
    • 10: Test Bank
    • 10: Labs
    • 10: Test Bank

  • Chapter 11: Comparing Two Populations or Treatments
    • 11: Concept Explorations
    • 11.1: Inferences Concerning the Difference Between Two Population or Treatment Means Using Independent Samples
    • 11.2: Inferences Concerning the Difference Between Two Population or Treatment Means Using Paired Samples
    • 11.3: Large-Sample Inferences Concerning the Difference Between Two Population or Treatment Proportions
    • 11.4: Interpreting and Communicating the Results of Statistical Analyses
    • 11.5: Simulation-Based Inference for Two Means (Optional)
    • 11.6: Simulation-Based Inference for Two Proportions (Optional)
    • 11: Chapter Review
    • 11: Active Examples
    • 11: Extra Problems
    • 11: JMP Simulations
    • 11: Concept Questions
    • 11: Labs
    • 11: Test Bank
    • 11: Labs
    • 11: Test Bank

  • Chapter 12: The Analysis of Categorical Data and Goodness-of-Fit Tests
    • 12: Concept Explorations
    • 12.1: Chi-Square Tests for Univariate Data
    • 12.2: Tests for Homogeneity and Independence in a Two-way Table
    • 12.3: Interpreting and Communicating the Results of Statistical Analyses
    • 12: Chapter Review
    • 12: Active Examples
    • 12: Extra Problems
    • 12: JMP Simulations
    • 12: Concept Questions
    • 12: Labs
    • 12: Test Bank

  • Chapter 13: Simple Linear Regression and Correlation: Inferential Methods
    • 13: Concept Explorations
    • 13.1: Simple Linear Regression Model
    • 13.2: Inferences About the Slope of the Population Regression Line
    • 13.3: Checking Model Adequacy
    • 13.4: Inferences Based on the Estimated Regression Line
    • 13.5: Inferences About the Population Correlation Coefficient
    • 13.6: Interpreting and Communicating the Results of Statistical Analyses
    • 13: Chapter Review
    • 13: Active Examples
    • 13: Cumulative Review Exercises
    • 13: Extra Problems
    • 13: JMP Simulations
    • 13: Concept Questions
    • 13: Labs
    • 13: Test Bank
    • 13: Labs
    • 13: Test Bank

  • Chapter 14: Multiple Regression Analysis
    • 14: Concept Explorations
    • 14.1: Multiple Regression Models
    • 14.2: Fitting a Model and Assessing Its Utility
    • 14.3: Inferences Based on an Estimated Model
    • 14.4: Other Issues in Multiple Regression
    • 14.5: Interpreting and Communicating the Results of Statistical Analyses
    • 14: Chapter Review
    • 14: Active Examples
    • 14: Extra Problems
    • 14: Concept Questions
    • 14: Labs
    • 14: Test Bank

  • Chapter 15: Analysis of Variance
    • 15: Concept Explorations
    • 15.1: Single-Factor ANOVA and the F Test
    • 15.2: Multiple Comparisons
    • 15.3: The F Test for a Randomized Block Experiment
    • 15.4: Two-Factor ANOVA
    • 15.5: Interpreting and Communicating the Results of Statistical Analyses
    • 15: Chapter Review
    • 15: Active Examples
    • 15: Extra Problems
    • 15: JMP Simulations
    • 15: Concept Questions
    • 15: Labs
    • 15: Test Bank

  • Chapter 16: Nonparametric (Distribution-Free) Statistical Methods
    • 16: Concept Explorations
    • 16.1: Distribution-Free Procedures for Inferences About a Difference Between Two Population or Treatment Means Using Independent Samples
    • 16.2: Distribution-Free Procedures for Inferences About a Difference Between Two Population or Treatment Means Using Paired Samples
    • 16.3: Distribution-Free ANOVA
    • 16: Chapter Review
    • 16: Active Examples
    • 16: Extra Problems
    • 16: Concept Questions
    • 16: Test Bank

  • 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: The Role of Statistics and the Data Analysis Process
1 0  
Chapter 2: Collecting Data Sensibly
2 0  
Chapter 3: Graphical Methods for Describing Data
3 0  
Chapter 4: Numerical Methods for Describing Data
4 0  
Chapter 5: Summarizing Bivariate Data
5 0  
Chapter 6: Probability
6 0  
Chapter 7: Random Variables and Probability Distributions
7 0  
Chapter 8: Sampling Variability and Sampling Distributions
8 0  
Chapter 9: Estimation Using a Single Sample
9 0  
Chapter 10: Hypothesis Testing Using a Single Sample
10 0  
Chapter 11: Comparing Two Populations or Treatments
11 0  
Chapter 12: The Analysis of Categorical Data and Goodness-of-Fit Tests
12 0  
Chapter 13: Simple Linear Regression and Correlation: Inferential Methods
13 0  
Chapter 14: Multiple Regression Analysis
14 0  
Chapter 15: Analysis of Variance
15 0  
Chapter 16: Nonparametric (Distribution-Free) Statistical Methods
16 0  
Total 0