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.

• 1. Introduction to Statistics2. Describing Data Sets3. Using Statistics to Summarize Data4. Probability5. Discrete Random Variables6. Normal Random Variables7. Distribution of sampling Statistics8. Statistical Estimation9. Testing Statistical Hypotheses10. Hypothesis Testing concerning two populations11. Analysis of Variance12. Linear Regression13. Chi-squared goodness of fit tests14. Nonparametric Hypothesis Tests15. Quality Control16. Machine Learning and Big Data

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