Probability, Statistics, and Information Theory for Scientists and Engineers

Probability, Statistics, and Information Theory for Scientists and Engineers offers students clear explanations of the most fundamental and useful statistical concepts. Extensively class-tested, the book is designed to appeal to the intuition, yet provide sound academic support, so that conclusions are clear and unambiguous. The text is a graphical introduction to the subject, which allows for ease of interpretation. In the first sections, students will explore the basic axioms and conclusions of probability and statistics. They will learn what can be expected in data taken from certain specified populations, and conversely, what can be inferred about a population from a data set. Unlike other standard texts, Probability, Statistics, and Information Theory for Scientists and Engineers also includes an introduction to information theory—the study of the structure of probability distributions. This allows for a new and useful perspective on hypothesis testing. Designed for science and engineering students, Probability, Statistics and Information Theory for Scientists and Engineers can be used in courses on engineering, math and statistics, and physics.