Statistics: The Art and Science of Learning from Data, Global Edition

PART I: GATHERING AND EXPLORING DATA

1. 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
2. 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
   • Chapter Summary
   • Chapter Exercises
3. 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
   • Chapter Summary
   • Chapter Exercises
4. 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
   • Chapter Summary
   • 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
• Chapter Summary
• Chapter Exercises

Random Variables and Probability Distributions

Alan Agresti is a Distinguished Professor Emeritus in the Department of Statistics at the University of Florida. He taught statistics there for 38 years, including the development of e-courses in statistical methods for social science students and three courses in categorical data analysis.

He is the author of more than 100 refereed articles and six texts, including Statistical Methods for the Social Sciences (Pearson, 5th edition, 2018) and An Introduction to Categorical Data Analysis (Wiley, 3rd edition, 2019). Alan has also received teaching awards from the University of Florida and an Excellence in Writing award from John Wiley & Sons.

Christine Franklin is the K-12 Statistics Ambassador for the American Statistical Association and elected ASA Fellow. She has retired from the University of Georgia as the Lothar Tresp Honoratus Honors Professor and Senior Lecturer Emerita in Statistics.

She is the co-author of two textbooks and has published more than 60 journal articles and book chapters. Chris was the lead writer for the American Statistical Association Pre-K-12 Guidelines for the Assessment and Instruction in Statistics Education (GAISE) Framework document, co-chair for the updated Pre-K-12 GAISE II, and chair of the ASA Statistical Education of Teachers (SET) report.

Bernhard Klingenberg is a Professor of Statistics in the Department of Mathematics & Statistics at Williams College, where he has been teaching introductory and advanced statistics classes since 2004. He teaches statistical inference and modelling as well as data visualisation at the Graduate Data Science Program at New College of Florida.