United States
£ GBP
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.
1. Preface
2. Introduction to Statistics
3. Describing Data Sets Using Statistics to Summarize
4. Data Sets Probability
5. Discrete Random Variables
6. Normal Random Variables
7. Distributions of Sampling
8. Statistics Estimation Testing
9. Statistical Hypotheses
10. Hypothesis Tests Concerning Two Populations
11. Analysis of Variance Linear Regression
12. Chi-Squared Goodness of Fit Tests
13. Nonparametric Hypotheses
14. Tests
15. Quality Control
16. Appendices
Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of Southern California. He received his Ph.D. 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, and a recipient of the Humboldt US Senior Scientist Award.
