Statistics with R 3/e

Robert Stinerock has more than 30 years of experience teaching statistics and probability to students at both the undergraduate and graduate level. He has taught classes at Columbia, Trinity, Rutgers, Fairleigh Dickinson, the Stevens Institute of Technology, Catolica de Lisboa (Portugal), and the Faculdade de Economia, Universidade Nova de Lisboa (Portugal). Since 2014, he has taught statistics at the Executive MBA program at Baruch College of the City University of New York. He has received several awards for excellence in the classroom: the Stevens Howe School Outstanding Undergraduate Teacher Award; the Stevens Alumni Association Outstanding Teacher Award; and the Fairleigh Dickinson Distinguished Faculty Award for Teaching. He has published numerous research articles in academic journals, most recently in the Journal of Macromarketing, the Journal of Business Research, and Geoforum. He earned his bachelor's, master's, and PhD degrees, all from Columbia University. He and his wife, Jyoti, live in New York City.

Chapter 1: Introduction and R Instructions Chapter 2: Descriptive Statistics: Tabular and Graphical Methods Chapter 3: Descriptive Statistics: Numerical Methods Chapter 4: Introduction to Probability Chapter 5: Discrete Probability Distributions Chapter 6: Continuous Probability Distributions Chapter 7: Point Estimation and Sampling Distributions Chapter 8: Confidence Interval Estimation Chapter 9: Hypothesis Tests: Basic Concepts and An Example Chapter 10: Hypothesis Tests about Means and Proportions: Applications Chapter 11: Comparisons of Means and Proportions Chapter 12: Simple Linear Regression Chapter 13: Multiple Regression

This book is a treasure for both instructors and students. It is written by a master, award-winning teacher with an unparalleled expertise of getting difficult concepts across in a deceptively simple fashion. Written in clear functional English, it both teaches the usual applied statistical methods, as well as provides a gentle introduction to Bayesian methods throughout the book. This is, in essence, more of a new book than just a new edition of an existing one. However, the features that made the first edition so successful have been retained: a student needs only basic algebra to understand the conceptual formulations that are illustrated with hands-on real-life examples that will appeal to students and motivate them to understand the importance of statistics in their daily lives. -- Swati Mukerjee Introduction to statistics is a busy field, and Stinerock explains the subject in a careful and friendly manner. The inclusion of Bayesian methods in the second edition is an important contribution - when it is encountered at the beginning of the statistical journey, it allows the reader to appreciate the richness of the Bayesian approach without dealing with the analytical and computational complexities of the subject. -- Eric Novik This book is a wonderful primer for learning both statistics and introductory R programming. It is clearly written, provides straightforward explanations of traditional and Bayesian methods, has a lot of supporting material for instructors and students including numerous practice data sets and solved exercises. -- Saroja Subrahmanyan