Introductory Statistics

We live in a data-driven world, and this is a book about understanding and working with that data. In order to be informed citizens, authors Rob Gould and Colleen Ryan believe that learning statistics extends beyond the classroom to an essential life skill. They teach students of all math backgrounds how to think about data, how to reason using data, and how to make decisions based on data. With a clear, unintimidating writing style and carefully chosen pedagogy,Introductory Statistics: Exploring the World through Data makes data analysis accessible to all students. Guided Exercises support students by building their confidence as they learn to solve problems. Snapshots summarize statistical procedures and concepts for convenient studying. While this text assumes the use of statistical software, formulas are presented as an aid to understanding the concepts rather than the focus of study. Check Your Tech features demonstrate how students will get the same numerical value by-hand as when using statistical software.1. Introduction to Data Case Study: Deadly Cell Phones? 1.1 What Are Data? 1.2 Classifying and Storing Data 1.3 Organizing Categorical Data 1.4 Collecting Data to Understand Causality Exploring Statistics: Collecting a Table of Different Kinds of Data 2. Picturing Variation with Graphs Case Study: Student-to-Teacher Ratio at Private and Public Colleges 2.1 Visualizing Variation in Numerical Data 2.2 Summarizing Important Features of a Numerical Distribution 2.3 Visualizing Variation in Categorical Variables 2.4 Summarizing Categorical Distributions 2.5 Interpreting Graphs Exploring Statistics: Personal Distance 3. Numerical Summaries of Center and Variation Case Study: Living in a Risky World 3.1 Summaries for Symmetric Distributions 3.2 What's Unusual? The Empirical Rule and z-Scores 3.3 Summaries for Skewed Distributions 3.4 Comparing Measures of Center 3.5 Using Boxplots for Displaying Summaries Exploring Statistics: Does Reaction Distance Depend on Gender? 4. Regression Analysis: Exploring Associations between Variables Case Study: Catching Meter Thieves 4.1 Visualizing Variability with a Scatterplot 4.2 Measuring Strength of Association with Correlation 4.3 Modeling Linear Trends 4.4 Evaluating the Linear Model Exploring Statistics: Guessing the Age of Famous People 5. Modeling Variation with Probability Case Study: SIDS or Murder? 5.1 What is Randomness? 5.2 Finding Theoretical Probabilities 5.3 Associations in Categorical Variables 5.4 Finding Empirical Probabilities with Simulations Exploring Statistics: "Let's Make a Deal": Stay or Switch? 6. Modeling Random Events: The Normal and Binomial Models Case Study: You Sometimes Get More Than You Pay For 6.1 Probability Distributions Are Models of Random Experiments 6.2 The Normal Model 6.3 The Binomial Model Exploring Statistics: ESP with Coin Flipping 7. Survey Sampling and Inference Case Study: Spring Break Fever: Just What the Doctors Ordered? 7.1 Learning about the World through Surveys 7.2 Measuring the Quality of a Survey 7.3 The Central Limit Theorem for Sample Proportions 7.4 Estimating the Population Proportion with Confidence Intervals 7.5 Margin of Error and Sample Size for Proportions (Optional) Exploring Statistics: Simple Random Sampling Prevents Bias 8. Hypothesis Testing for Population Proportions Case Study: Does Watching Violent TV as a Child Lead to Violent Behavior as an Adult? 8.1 The Main Ingredients of Hypothesis Testing 8.2 Characterizing p-values 8.3 Hypothesis Testing in Four Steps 8.4 Comparing Proportions from Two Populations 8.5 Understanding Hypothesis Testing Exploring Statistics: Identifying Flavors of Gum through Smell 9. Inferring Population Means Case Study: Epilepsy Drugs and Children 9.1 Sample Means of Random Samples 9.2 The Central Limit Theorem for Sample Means 9.3 Answering Questions about the Mean of a Population 9.4 Comparing Two Population Means 9.5 Overview of Analyzing Means Exploring Statistics: Pulse Rates 10. Associations between Categorical Variables Case Study: Popping Better Popcorn 10.1 The Basic Ingredients for Testing with Categorical Variables 10.2 The Chi-Square Test for Goodness of Fit 10.3 Chi-Square Tests for Associations between Categorical Variables 10.4 Hypothesis Tests When Sample Sizes Are Small Exploring Statistics: Skittles 11. Multiple Comparisons and Analysis of Variance Case Study: Seeing Red 11.1 Multiple Comparisons 11.2 The Analysis of Variance 11.3 The ANOVA Test 11.4 Post-Hoc Procedures Exploring Statistics: Recovery Heart Rate 12. Experimental Design: Controlling Variation Case Study: Does Stretching Improve Athletic Performance? 12.1 Variation Out of Control 12.2 Controlling Variation in Surveys 12.3 Reading Research Papers Exploring Statistics: Reporting on Research Activities 13. Inference without Normality Case Study: Electric Rays 13.1 Transforming Data 13.2 The Sign Test for Paired Data 13.3 Mann-Whitney Test for Two Independent Groups 13.4 Randomization Tests Exploring Statistics: Balancing on One Foot 14. Inference for Regression Case Study: Building a Better Oyster Shucker 14.1 The Linear Regression Model 14.2 Using the Linear Model 14.3 Predicting Values and Estimating Means Exploring Statistics: Older and Slower?