Statistics: The Exploration and Analysis of Data 7th edition

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

• Chapter 1: The Role of Statistics and the Data Analysis Process
  • 1.1: 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: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 2: Collecting Data Sensibly
  • 2.1: Statistical Studies: Observation and Experimentation
  • 2.2: Sampling
  • 2.3: Simple Comparative Experiments
  • 2.4: More on Experimental Design
  • 2.5: More on Observational Studies: Designing Surveys (Optional)
  • 2.6: Interpreting and Communicating the Results of Statistical Analyses
  • 2: Chapter Review
  • 2: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 3: Graphical Methods for Describing Data
  • 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: Cumulative Review Exercises
  • 3: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 4: Numerical Methods for Describing Data
  • 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: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 5: Summarizing Bivariate Data
  • 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: Logistic Regression (Optional)
  • 5.6: Interpreting and Communicating the Results of Statistical Analyses
  • 5: Chapter Review
  • 5: Cumulative Review Exercises
  • 5: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 6: Probability
  • 6.1: Interpreting Probabilities and Basic Probability Rules
  • 6.2: Probability as a Basis for Making Decisions
  • 6.3: Estimating Probabilities Empirically and by Using Simulation
  • 6: Chapter Review
  • 6: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 7: Population Distributions
  • 7.1: Describing the Distribution of Values in a Population
  • 7.2: Population Models for Continuous Numerical Variables
  • 7.3: Normal Distributions
  • 7.4: Checking for Normality and Normalizing Transformations
  • 7: Chapter Review
  • 7: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 8: Sampling Variability and Sampling Distributions
  • 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: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 9: Estimation Using a Single Sample
  • 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: Chapter Review
  • 9: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 10: Hypothesis Testing Using a Single Sample
  • 10.1: Hypotheses and Test Procedures
  • 10.2: Errors in Hypothesis 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: Chapter Review
  • 10: Cumulative Review Exercises
  • 10: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 11: Comparing Two Populations or Treatments
  • 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 a Difference Between Two Population or Treatment Proportions
  • 11.4: Interpreting and Communicating the Results of Statistical Analyses
  • 11: Chapter Review
  • 11: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 12: The Analysis of Categorical Data and Goodness-of-Fit Tests
  • 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: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 13: Simple Linear Regression and Correlation: Inferential Methods
  • 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 (Optional)
  • 13.5: Inferences About the Population Correlation Coefficient (Optional)
  • 13.6: Interpreting and Communicating the Results of Statistical Analyses
  • 13: Chapter Review
  • 13: Cumulative Review Exercises
  • 13: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 14: Multiple Regression Analysis
  • 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: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 15: Analysis of Variance
  • 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: Extra Problems
  • Active Examples
  • Active Examples
  
  
• Chapter 16: Nonparametric (Distribution-Free) Statistical Methods
  • 16.1: Distribution-Free Procedures for Inferences About a Difference Between Two Population or Treatment Means Using Independent Samples (Optional)
  • 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: Extra Problems
  • Active Examples
  • Active Examples