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.Prof. Klingenberg is responsible for the development of the web apps, which he programs using the R package Shiny. A native of Austria, he frequently returns there to hold visiting positions at universities and gives short courses on categorical data analysis in Europe and the United States. He also enjoys photography, with some of his pictures appearing in this book.

• PART I: GATHERING AND EXPLORING DATA Statistics: The Art and Science of Learning from DataExploring Data with Graphs and Numerical SummariesExploring Relationships Between Two VariablesGathering DataPART II: PROBABILITY, PROBABILITY DISTRIBUTIONS, AND SAMPLING DISTRIBUTIONS Probability in Our Daily LivesSampling DistributionsPART III: INFERENTIAL STATISTICS Statistical Inference: Confidence IntervalsStatistical Inference: Significance Tests About HypothesesComparing Two GroupsPART IV: ANALYZING ASSOCIATION AND EXTENDED STATISTICAL METHODS Analyzing the Association Between Categorical VariablesAnalyzing the Association Between Quantitative Variables: Regression AnalysisMultiple RegressionComparing Groups: Analysis of Variance MethodsNonparametric Statistics

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.Prof. Klingenberg is responsible for the development of the web apps, which he programs using the R package Shiny. A native of Austria, he frequently returns there to hold visiting positions at universities and gives short courses on categorical data analysis in Europe and the United States. He also enjoys photography, with some of his pictures appearing in this book.

• PART I: GATHERING AND EXPLORING DATA Statistics: The Art and Science of Learning from DataExploring Data with Graphs and Numerical SummariesExploring Relationships Between Two VariablesGathering DataPART II: PROBABILITY, PROBABILITY DISTRIBUTIONS, AND SAMPLING DISTRIBUTIONS Probability in Our Daily LivesSampling DistributionsPART III: INFERENTIAL STATISTICS Statistical Inference: Confidence IntervalsStatistical Inference: Significance Tests About HypothesesComparing Two GroupsPART IV: ANALYZING ASSOCIATION AND EXTENDED STATISTICAL METHODS Analyzing the Association Between Categorical VariablesAnalyzing the Association Between Quantitative Variables: Regression AnalysisMultiple RegressionComparing Groups: Analysis of Variance MethodsNonparametric Statistics

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.Prof. Klingenberg is responsible for the development of the web apps, which he programs using the R package Shiny. A native of Austria, he frequently returns there to hold visiting positions at universities and gives short courses on categorical data analysis in Europe and the United States. He also enjoys photography, with some of his pictures appearing in this book.

• PART I: GATHERING AND EXPLORING DATA Statistics: The Art and Science of Learning from DataExploring Data with Graphs and Numerical SummariesExploring Relationships Between Two VariablesGathering DataPART II: PROBABILITY, PROBABILITY DISTRIBUTIONS, AND SAMPLING DISTRIBUTIONS Probability in Our Daily LivesSampling DistributionsPART III: INFERENTIAL STATISTICS Statistical Inference: Confidence IntervalsStatistical Inference: Significance Tests About HypothesesComparing Two GroupsPART IV: ANALYZING ASSOCIATION AND EXTENDED STATISTICAL METHODS Analyzing the Association Between Categorical VariablesAnalyzing the Association Between Quantitative Variables: Regression AnalysisMultiple RegressionComparing Groups: Analysis of Variance MethodsNonparametric Statistics