About the Book

For courses in introductory statistics.

This is the 24-month standalone access card for MyLab Statistics.

The art and science of learning from data

Statistics: The Art and Science of Learning from Data takes a conceptual approach, helping students understand what statistics is about and learning the right questions to ask when analyzing data, rather than just memorizing procedures. This book takes the ideas that have turned statistics into a central science in modern life and makes them accessible, without compromising the necessary rigor. Students will enjoy reading this book, and will stay engaged with its wide variety of real-world data in the examples and exercises.

The authors believe that it's important for students to learn and analyze both quantitative and categorical data. As a result, the text pays greater attention to the analysis of proportions than many other introductory statistics texts. Concepts are introduced first with categorical data, and then with quantitative data. The 5th Edition enhances the student and instructor experience and provides a more accessible introduction to statistical thinking and practice.

Personalize learning with MyLab Statistics

MyLab(TM) Statistics is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab Statistics personalizes the learning experience and improves results for each student. With MyLab Statistics and StatCrunch^(R), integrated web-based statistical software, students learn the skills they need to interact with data in the real world.

0136679129 / 9780136679127 MYLAB STATISTICS WITH PEARSON ETEXT -- STANDALONE ACCESS CARD -- FOR STATISTICS: THE ART AND SCIENCE OF LEARNING FROM DATA -- 24 MONTHS, 5/e

About the Author: Alan Agresti is Distinguished Professor Emeritus in the Department of Statistics at the University of Florida. He taught statistics there for 38 years, including the development of three courses in statistical methods for social science students and three courses in categorical data analysis. He is 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). He is a Fellow of the American Statistical Association and recipient of an Honorary Doctor of Science from De Montfort University in the UK. He has held visiting positions at Harvard University, Boston University, the London School of Economics, and Imperial College and has taught courses or short courses for universities and companies in about 30 countries worldwide. He 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 is 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 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. She is a past Chief Reader for Advance Placement Statistics, a Fulbright scholar to New Zealand (2015), recipient of the United States Conference on Teaching Statistics (USCOTS) Lifetime Achievement Award, the ASA Founder's award and an elected member of the International Statistical Institute (ISI). Chris loves being with her family, running, hiking, scoring baseball games, and reading mysteries.

Bernhard Klingenberg is Professor of Statistics in the Department of Mathematics & Statistics at Williams College, where he has been teaching introductory and advanced statistics classes since 2004, and in the Graduate Data Science Program at New College of Florida, where he enjoys teaching statistical inference and modeling as well as data visualization. Bernhard is responsible for the development of the web apps, which he programs using the R package shiny. A native of Austria, Bernhard frequently returns there to hold visiting positions at universities and gives short courses on categorical data analysis in Europe and the United States. He has published several peer-reviewed articles in statistical journals and consults regularly with academia and industry. Bernhard enjoys photography (some of his pictures appear in this book), scuba diving, hiking state parks in Florida, and spending time with his wife and four children.