Introductory Statistics

ISBN-13: 9780128043172 / Angielski / Twarda / 2017 / 828 str.

Sheldon M. Ross

Opis

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 real-world 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 80-20 rule, Benford's law, added material on odds and joint distributions and correlation, logistic regression, A-B testing, and more modern (big data) examples and exercises.

• Includes new section on Pareto distribution and the 80-20 rule, Benford's law, odds, joint distribution and correlation, logistic regression, A-B 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), ISM, SSM, and an online graphing calculator manual
• 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

Recenzje

"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

Spis treści

1. Preface2. Introduction to Statistics3. Describing Data Sets Using Statistics to Summarize4. Data Sets Probability5. Discrete Random Variables6. Normal Random Variables7. Distributions of Sampling8. Statistics Estimation Testing9. Statistical Hypotheses10. Hypothesis Tests Concerning Two Populations11. Analysis of Variance Linear Regression12. Chi-Squared Goodness of Fit Tests13. Nonparametric Hypotheses14. Tests15. Quality Control16. Appendices

O autorze

Dr. Sheldon M. Ross is a professor in the Department of Industrial and Systems Engineering at the University of Southern California. He received his PhD in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, a Fellow of INFORMS, and a recipient of the Humboldt US Senior Scientist Award.