Statistics: The Art and Science of Learning from Data, 5th edition
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Overview
Statistics teaches the art and science of learning from data. Accessible, realworld examples help you gain a true grasp of statistical thinking, instead of just memorizing procedures.
Published by Pearson (August 4th 2021)  Copyright © 2021
ISBN13: 9780136879992
Subject: Introductory Statistics
Category: Statistics: The Art and Science of Learning from Data
Table of contents
 Preface
I: GATHERING AND EXPLORING DATA
 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
 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
 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
 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
II: PROBABILITY, PROBABILITY DISTRIBUTIONS, AND SAMPLING DISTRIBUTIONS
 Probability in Our Daily Lives
 5.1 How Probability Quantifies Randomness
 5.2 Finding Probabilities
 5.3 Conditional Probability
 5.4 Applying the Probability Rules
 Chapter Summary
 Chapter Exercises
 Random Variables and Probability Distributions
 6.1 Summarizing Possible Outcomes and Their Probabilities
 6.2 Probabilities for BellShaped Distributions
 6.3 Probabilities When Each Observation Has Two Possible Outcomes
 Chapter Summary
 Chapter Exercises
 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
III: INFERENTIAL STATISTICS
 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
 Statistical Inference: Significance Tests About Hypotheses
 9.1 Steps for Performing a Significance Test
 9.2 Significance Tests About Proportions
 9.3 Significance Tests 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
 Chapter Summary
 Chapter Exercises
 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
IV: ANALYZING ASSOCIATION AND EXTENDED STATISTICAL METHODS
 Analyzing the Association Between Categorical Variables
 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
 Analyzing the Association Between Quantitative Variables: Regression Analysis
 12.1 Modeling How Two Variables Are Related
 12.2 Inference About Model Parameters and the Association
 12.3 Describing the Strength of Association
 12.4 How the Data Vary Around the Regression Line
 12.5 Exponential Regression: A Model for Nonlinearity
 Chapter Summary
 Chapter Exercises
 Multiple Regression
 13.1 Using Several Variables to Predict a Response
 13.2 Extending the Correlation and R2 for Multiple Regression
 13.3 Using Multiple Regression to Make Inferences
 13.4 Checking a Regression Model Using Residual Plots
 13.5 Regression and Categorical Predictors
 13.6 Modeling a Categorical Response
 Chapter Summary
 Chapter Exercises
 Comparing Groups: Analysis of Variance Methods
 14.1 OneWay ANOVA: Comparing Several Means
 14.2 Estimating Differences in Groups for a Single Factor
 14.3 TwoWay ANOVA
 Chapter Summary
 Chapter Exercises
 Nonparametric Statistics
 15.1 Compare Two Groups by Ranking
 15.2 Nonparametric Methods for Several Groups and for Matched Pairs
 Chapter Summary
 Chapter Exercises
Appendix
Answers
Index
Index of Applications
Credits
Your questions answered
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