Efnisyfirlit

• Title Page
• Copyright
• Dedication
• Contents
• An Introduction to the Web Apps
• Preface
• About the Authors
• Part One: Gathering and Exploring Data
  • Chapter 1. Statistics: The Art and Science of Learning From Data
    • 1.1 Using Data to Answer Statistical Questions
    • 1.2 Sample Versus Population
    • 1.3 Organizing Data, Statistical Software, and the New Field of Data Science
    • Chapter Summary
    • Chapter Exercises
  • Chapter 2. Exploring Data With Graphs and Numerical Summaries
    • 2.1 Different Types of Data
    • 2.2 Graphical Summaries of Data
    • 2.3 Measuring the Center of Quantitative Data
    • 2.4 Measuring the Variability of Quantitative Data
    • 2.5 Using Measures of Position to Describe Variability
    • 2.6 Linear Transformations and Standardizing
    • 2.7 Recognizing and Avoiding Misuses of Graphical Summaries
    • Chapter Summary
    • Chapter Exercises
  • Chapter 3. Exploring Relationships Between Two Variables
    • 3.1 The Association Between Two Categorical Variables
    • 3.2 The Relationship Between Two Quantitative Variables
    • 3.3 Linear Regression: Predicting the Outcome of a Variable
    • 3.4 Cautions in Analyzing Associations
    • Chapter Summary
    • Chapter Exercises
  • Chapter 4. Gathering Data
    • 4.1 Experimental and Observational Studies
    • 4.2 Good and Poor Ways to Sample
    • 4.3 Good and Poor Ways to Experiment
    • 4.4 Other Ways to Conduct Experimental and Nonexperimental Studies
    • Chapter Summary
    • Chapter Exercises
• Part Two: Probability, Probability Distributions, and Sampling Distributions
  • Chapter 5. Probability in Our DailyLives
    • 5.1 How Probability Quantifies Randomness
    • 5.2 Finding Probabilities
    • 5.3 Conditional Probability
    • 5.4 Applying the Probability Rules
    • Chapter Summary
    • Chapter Exercises
  • Chapter 6. Random Variables and Probability Distributions
    • 6.1 Summarizing Possible Outcomes and Their Probabilities
    • 6.2 Probabilities for Bell-Shaped Distributions: The Normal Distribution
    • 6.3 Probabilities When Each Observation Has Two Possible Outcomes: The Binomial Distribution
    • Chapter Summary
    • Chapter Exercises
  • Chapter 7. Sampling Distributions
    • 7.1 How Sample Proportions Vary Around the Population Proportion
    • 7.2 How Sample Means Vary Around the Population Mean
    • 7.3 Using the Bootstrap to Find Sampling Distributions
    • Chapter Summary
    • Chapter Exercises
• Part Three: Inferential Statistics
  • Chapter 8. Statistical Inference: Confidence Intervals
    • 8.1 Point and Interval Estimates of Population Parameters
    • 8.2 Confidence Interval for a Population Proportion
    • 8.3 Confidence Interval for a Population Mean
    • 8.4 Bootstrap Confidence Intervals
    • Chapter Summary
    • Chapter Exercises
  • Chapter 9. Statistical Inference: Significance Tests About Hypotheses
    • 9.1 Steps for Performing a Significance Test
    • 9.2 Significance Test About a Proportion
    • 9.3 Significance Test About a Mean
    • 9.4 Decisions and Types of Errors in Significance Tests
    • 9.5 Limitations of Significance Tests
    • 9.6 The Likelihood of a Type II Error and the Power of a Test
    • Chapter Summary
    • Chapter Exercises
  • Chapter 10. Comparing Two Groups
    • 10.1 Categorical Response: Comparing Two Proportions
    • 10.2 Quantitative Response: Comparing Two Means
    • 10.3 Comparing Two Groups With Bootstrap or Permutation Resampling
    • 10.4 Analyzing Dependent Samples
    • 10.5 Adjusting for the Effects of Other Variables
    • Chapter Summary
    • Chapter Exercises
• Part Four: Extended Statistical Methods and Models for Analyzing Categorical and Quantitative Variab
  • Chapter 11. Categorical Data Analysis
    • 11.1 Independence and Dependence (Association)
    • 11.2 Testing Categorical Variables for Independence
    • 11.3 Determining the Strength of the Association
    • 11.4 Using Residuals to Reveal the Pattern of Association
    • 11.5 Fisher’s Exact and Permutation Tests
    • Chapter Summary
    • Chapter Exercises
  • Chapter 12. Regression Analysis
    • 12.1 The Linear Regression Model
    • 12.2 Inference About Model Parameters and the Relationship
    • 12.3 Describing the Strength of the Relationship
    • 12.4 How the Data Vary Around the Regression Line
    • 12.5 Exponential Regression: A Model for Nonlinearity
    • Chapter Summary
    • Chapter Exercises
  • Chapter 13. Multiple Regression
    • 13.1 Using Several Variables to Predict a Response
    • 13.2 Extending the Correlation Coefficient and R2 for Multiple Regression
    • 13.3 Inferences Using Multiple Regression
    • 13.4 Checking a Regression Model Using Residual Plots
    • 13.5 Regression and Categorical Predictors
    • 13.6 Modeling a Categorical Response: Logistic Regression
    • Chapter Summary
    • Chapter Exercises
  • Chapter 14. Comparing Groups: Analysis of Variance Methods
    • 14.1 One-Way ANOVA: Comparing Several Means
    • 14.2 Estimating Differences in Groups for a Single Factor
    • 14.3 Two-Way ANOVA: Exploring Two Factors and Their Interaction
    • Chapter Summary
    • Chapter Exercises
  • Chapter 15. Nonparametric Statistics
    • 15.1 Compare Two Groups by Ranking
    • 15.2 Nonparametric Methods for Several Groups and for Dependent Samples
    • Chapter Summary
    • Chapter Exercises
• Appendix
• Answers
• Index
  • A
  • B
  • C
  • D
  • E
  • F
  • G
  • H
  • I
  • J
  • K
  • L
  • M
  • N
  • O
  • P
  • Q
  • R
  • S
  • T
  • U
  • V
  • W
  • X
  • Y
  • Z
• Index of Applications
  • A
  • B
  • C
  • D
  • E
  • F
  • G
  • H
  • I
  • J
  • K
  • L
  • M
  • N
  • O
  • P
  • Q
  • R
  • S
  • T
  • U
  • V
  • W
• Credits

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