This text combines the topics generally found in main-stream elementary statistics books with the essentials of the underlying theory. The book begins with an axiomatic treatment of probability followed by chapters on discrete and continuous random variables and their associated distributions. It then introduces basic statistical concepts including summarizing data and interval parameter estimation, stressing the connection between probability and statistics. Final chapters introduce hypothesis testing, regression, and non-parametric techniques. All chapters provide a balance between conceptual understanding and theoretical understanding of the topics at hand.

From SAT scores to job search methods, statistics influences and shapes the world around us. Marty Triola's text continues to be the bestseller because it helps students understand the relationship between statistics and the world, bringing life to the theory and methods. Essentials of Statistics (a briefer version of Elementary Statistics-see below for the full series) raises the bar with every edition by incorporating an unprecedented amount of real and interesting data that will help instructors connect with students today, and help them connect statistics to their daily lives. The Fifth Edition contains more than 1,585 exercises, 89% of which use real data and 86% of which are new.

The authors are proud sponsors of the 2020 SAGE Keith Roberts Teaching Innovations Award—enabling graduate students and early career faculty to attend the annual ASA pre-conference teaching and learning workshop. Essentials of Social Statistics for a Diverse Society, Third Edition, is a more streamlined, less expensive version of the successful Social Statistics for a Diverse Society. As in the parent text, the Essentials version does more than introduce students to the statistical techniques used by social scientists. It is distinct for the use of real data from contemporary social issues, illustrating the interplay between social concerns and methods of inquiry, and for a strong emphasis on race, class, gender, and other statuses to show how statistics can be a tool for understanding the richness of social differences within society. With a wide range of examples and exercises taken from current events and published research, frequent illustrations, and a focus on student learning, this book continues to be an accessible and engaging resource for students. "I think this textbook is incredibly readable. It presents statistics in a manner that is easy to grasp and comprehend but is still rigorous in terms of the content covered." —Amy Lucas, University of Houston–Clear Lake A Complete Teaching & Learning Package SAGE edge FREE online resources for students that make learning easier. See how your students benefit.

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data