A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."—Technometrics

Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of:

More than 250 exercises—with selected "hints"—scattered throughout to stimulate readers' thinking and to actively engage them in applying their newfound skills

An increased focus on why a method is introduced

Multiple explanations of basic concepts

Real-life applications in a variety of disciplines

Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications

Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.

- Cover
- Title page
- Copyright page
- Preface
- Chapter 1 Variation
- Chapter 2 Probability
- Chapter 3 Two Naturally Occurring Probability Distributions
- Chapter 4 Estimation and the Normal Distribution
- Chapter 5 Testing Hypotheses
- Chapter 6 Designing an Experiment or Survey
- Chapter 7 Guide to Entering, Editing, Saving, and Retrieving Large Quantities of Data Using R
- Chapter 8 Analyzing Complex Experiments
- Chapter 9 Developing Models
- Chapter 10 Reporting Your Findings
- Chapter 11 Problem Solving
- Answers to Selected Exercises
- Index