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Textbook in PDF format
Introductory Statistics: Exploring the World Through Data helps you learn to think critically with and about data, communicate your findings to others, and evaluate others’ arguments carefully. Crafted by authors who are active in the classroom and in the statistics education community, it combines clear, conversational writing with new and frequent opportunities to apply what you’ve learned. The 4th Edition fully revises end-of-chapter Data Projects, updates technology guides to match current hardware and software, adds hundreds of new exercises and updates previous exercises, and much more.
Preface
Introduction to Data
Case study: Dangerous Habit?
What Are Data?
Classifying and Storing Data
Investigating Data
Organizing Categorical Data
Collecting Data to Understand Causality
Data project: Introduction: Importing Data
Picturing Variation with Graphs
Case study: Student-to-Teacher Ratio at Colleges
Visualizing Variation in Numerical Data
Summarizing Important Features of a Numerical Distribution
Visualizing Variation in Categorical Variables
Summarizing Categorical Distributions
Interpreting Graphs
Data project: The Bare Bones: Data Types
Numerical Summaries of Center and Variation
Case study: Living in a Risky World
Summaries for Symmetric Distributions
What’s Unusual? The Empirical Rule and z-Scores
Summaries for Skewed Distributions
Comparing Measures of Center
Using Boxplots for Displaying Summaries
Data project: The W’s and One H: Asking Interrogative Questions
Regression Analysis: Exploring Associations between Variables
Case study: Forecasting Home Prices
Visualizing Variability with a Scatterplot
Measuring Strength of Association with Correlation
Modeling Linear Trends
Evaluating the Linear Model
Data project: Get it Sorted: Sorting Data
Modeling Variation with Probability
Case study: SIDS or Murder?
What Is Randomness?
Finding Theoretical Probabilities
Associations in Categorical Variables
Finding Empirical and Simulated Probabilities
Data project: Ask Good Questions: Posing Statistical Investigative Questions
Modeling Random Events: The Normal and Binomial Models
Case study: You Sometimes Get More Than You Pay for
Probability Distributions Are Models of Random Experiments
The Normal Model
The Binomial Model
Data project: Transformations for a Better Analysis
Survey Sampling and Inference
Case study: Spring Break Fever: Just What the Doctors Ordered?
Learning about the World through Surveys
Measuring the Quality of a Survey
The Central Limit Theorem for Sample Proportions
Estimating the Population Proportion with Confidence Intervals
Comparing Two Population Proportions with Confidence
Data project: Make it Smaller: Subsetting Data
Hypothesis Testing for Population Proportions
Case study: Dodging the Question
The Essential Ingredients of Hypothesis Testing
Hypothesis Testing in Four Steps
Hypothesis Tests in Detail
Comparing Proportions from Two Populations
Data project: On and Off, and Off and On: Working with Binary Variables
Inferring Population Means
Case study: You Look Sick! Are You Sick?
Sample Means of Random Samples
The Central Limit Theorem for Sample Means
Answering Questions about the Mean of a Population
Hypothesis Testing for Means
Comparing Two Population Means
Overview of Analyzing Means
Data project: Non-binary Coding: Creating Multi-valued Categorical Variables
Associations between Categorical Variables
Case study: Popping Better Popcorn 506
The Basic Ingredients for Testing with Categorical Variables
The Chi-Square Test for Goodness of Fit
Chi-Square Tests for Associations between Categorical Variables
Hypothesis Tests When Sample Sizes Are Small
Data project: Dating Yourself: Creating New Variables from Dates
Multiple Comparisons and Analysis of Variance
Case study: Seeing Red
Multiple Comparisons
The Analysis of Variance
The ANOVA Test
Post Hoc Procedures
Data project: What’s in a Name: Splitting and Merging Columns
Experimental Design: Controlling Variation
Case study: Does Stretching Improve Athletic Performance?
Variation Out of Control
Controlling Variation in Surveys
Reading Research Papers
Data project: Making Stacks: Stacking and Unstacking Data
Inference without Normality
Case study: Contagious Yawns
Transforming Data
The Sign Test for Paired Data
Mann-Whitney Test for Two Independent Groups
Randomization Tests
Data project: Breathe Deeply: Prepare a Data Set for Analysis
Inference for Regression
Case study: Another Reason to Stand at Your Desk?
The Linear Regression Model
Using the Linear Model
Predicting Values and Estimating Means
Data project: Is the Pen Mightier than the Keyboard?
Appendix A Tables A-1
Appendix B Answers to Odd-Numbered Exercises A-9
Subject Index I-1
Index of Application Areas I-8
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