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PART I: GATHERING AND EXPLORING DATA Statistics: The Art and Science of Learning from Data Using Data to Answer Statistical Questions Sample Versus Population Organizing Data, Statistical Software, and the New Field of Data Science
Chapter Summary
Chapter Exercises Exploring Data with Graphs and Numerical Summaries Different Types of Data Graphical Summaries of Data Measuring the Center of Quantitative Data Measuring the Variability of Quantitative Data Using Measures of Position to Describe Variability Linear Transformations and Standardizing Recognizing and Avoiding Misuses of Graphical Summaries
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Chapter Exercises Exploring Relationships Between Two Variables The Association Between Two Categorical Variables The Relationship Between Two Quantitative Variables Linear Regression: Predicting the Outcome of a Variable Cautions in Analyzing Associations
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Chapter Exercises Gathering Data Experimental and Observational Studies Good and Poor Ways to Sample Good and Poor Ways to Experiment Other Ways to Conduct Experimental and Nonexperimental Studies
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Chapter Exercises
PART II: PROBABILITY, PROBABILITY DISTRIBUTIONS, AND SAMPLINGDISTRIBUTIONS Probability in Our Daily Lives How Probability Quantifies Randomness Finding Probabilities Conditional Probability Applying the Probability Rules
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Chapter Exercises Random Variables and Probability Distributions Summarizing Possible Outcomes and Their Probabilities Probabilities for Bell-Shaped Distributions Probabilities When Each Observation Has Two Possible Outcomes
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Chapter Exercises Sampling Distributions How Sample Proportions Vary Around the Population Proportion How Sample Means Vary Around the Population Mean Using the Bootstrap to Find Sampling Distributions
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Chapter Exercises
PART III: INFERENTIAL STATISTICS Statistical Inference: Confidence Intervals Point and Interval Estimates of Population Parameters Confidence Interval for a Population Proportion Confidence Interval for a Population Mean Bootstrap Confidence Intervals
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Chapter Exercises Statistical Inference: Significance Tests About Hypotheses Steps for Performing a Significance Test Significance Tests About Proportions Significance Tests About a Mean Decisions and Types of Errors in Significance Tests Limitations of Significance Tests The Likelihood of a Type II Error
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Chapter Exercises Comparing Two Groups Categorical Response: Comparing Two Proportions Quantitative Response: Comparing Two Means Comparing Two Groups with Bootstrap or Permutation Resampling Analyzing Dependent Samples Adjusting for the Effects of Other Variables
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Chapter Exercises
PART IV: ANALYZING ASSOCIATION AND EXTENDED STATISTICALMETHODS Analyzing the Association Between Categorical Variables Independence and Dependence (Association) Testing Categorical Variables for Independence Determining the Strength of the Association Using Residuals to Reveal the Pattern of Association Fisher''s Exact and Permutation Tests
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Chapter Exercises Analyzing the Association Between Quantitative Variables: Regression Analysis Modeling How Two Variables Are Related Inference About Model Parameters and the Association Describing the Strength of Association How the Data Vary Around the Regression Line Exponential Regression: A Model for Nonlinearity
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Chapter Exercises Multiple Regression Using Several Variables to Predict a Response Extending the Correlation and R2 for Multiple Regression Using Multiple Regression to Make Inferences Checking a Regression Model Using Residual Plots Regression and Categorical Predictors Modeling a Categorical Response
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Chapter Exercises Comparing Groups: Analysis of Variance Methods One-Way ANOVA: Comparing Several Means Estimating Differences in Groups for a Single Factor Two-Way ANOVA
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Chapter Exercises Nonparametric Statistics Compare Two Groups by Ranking Nonparametric Methods for Several Groups and for Matched Pairs
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Chapter Exercises Appendix Answers Index Index of Applications Credits

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