












Key Features
 Includes new section on Pareto distribution and the 8020 rule, Benford’s law, odds, joint distribution and correlation, logistic regression, AB testing, and examples from the world of analytics and big data
 Comprehensive edition that includes the most commonly used statistical software packages (SAS, SPSS, Minitab)
 Presents a unique, historical perspective, profiling prominent statisticians and historical events to motivate learning by including interest and context
 Provides exercises and examples that help guide the student towards indpendent learning using real issues and real data, e.g. stock price models, health issues, gender issues, sports, and scientific fraud

About the Book
Introductory Statistics, Fourth Edition, reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedures should be used. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, an explanation of intuition, and the ideas behind the statistical methods.
Concepts are motivated, illustrated, and explained in a way that attempts to increase one's intuition. To quote from the preface, it is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions, and examples.
Applications and examples refer to realworld issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud, and many others. Examples relating to data mining techniques using the number of Google queries or Twitter tweets are also considered.
For this fourth edition, new topical coverage includes sections on Pareto distribution and the 8020 rule, Benford's law, added material on odds and joint distributions and correlation, logistic regression, AB testing, and more modern (big data) examples and exercises.
Readership
This text is written for the introductory noncalculus based statistics course offered in mathematics and/or statistics departments for undergraduate students of any major who take a semester course in basic Statistics or a year course in Probability and Statistics
Quotes
"The coverage is careful and slow, with many worked examples and plenty of problems, half of which have answers. ...Illuminating examples abound. Those who are less than wholly confident about any of the material will find it a rich and unthreatening resource of information and also of questions (even if they are almost all derived from a US context). I have been looking for some time for a properly academic superior to M.J. Moroney’s invaluable if outdated Facts from figures which I have used for forty years, and this would seem to fill the bill." The Mathematical Gazette
"There are some interesting topics included that are not in most introductory stats texts, such as the Gini index, bandit problems, and quality control." MAA Reviews
Content View Table of Contents




