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Informationen zum Autor 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.
List of contents
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
Report
"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 I have been looking for some time for a properly academic superior to M.J. Moroney's invaluable if outdated Facts from figures which I have used for forty years, and this would seem to fill the bill."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
