First Course in Probability, A, Global Edition

Sheldon Ross  
Total pages
September 2019
Related Titles


For upper-level to graduate courses in Probability or Probability and Statistics, for majors in mathematics, statistics, engineering, and the sciences.

Explores both the mathematics and the many potential applications of probability theory

A First Course in Probability offers an elementary introduction to the theory of probability for students in mathematics, statistics, engineering, and the sciences. Through clear and intuitive explanations, it attempts to present not only the mathematics of probability theory, but also the many diverse possible applications of this subject through numerous examples. The 10th Edition includes many new and updated problems, exercises, and text material chosen both for inherent interest and for use in building student intuition about probability.


Hallmark Features

  • Analysis is unique to the text and elegantly designed. Examples include the knockout tournament and multiple players gambling ruin problem, along with results concerning the sum of uniform and the sum of geometric random variables.
  • Intuitive explanations are supported with an abundance of examples to give readers a thorough introduction to both the theory and applications of probability.
  • Examples such as Example 4n of Chapter 3, which deals with computing NCAA basketball tournament win probabilities, and Example 5b of Chapter 4, which introduces the friendship paradox.
  • Self-Test Problems and Exercises include complete solutions in the appendix, allowing students to test their comprehension and study for exam

New to this Edition

New and Updated Features

  • Increased clarity of exposition throughout.
  • Many new and updated problems.
  • New and updated exercises and text material — chosen for interest value and to build student intuition about probability — including:
    • Computing NCAA basketball tournament win probabilities
    • The friendship paradox
    • New material on the Pareto distribution
    • New material on Poisson limit results
    • New material on the Lorenz curve

Table of Contents

  1. Combinatorial Analysis
  2. Axioms of Probability
  3. Conditional Probability and Independence
  4. Random Variables
  5. Continuous Random Variables
  6. Jointly Distributed Random Variables
  7. Properties of Expectation
  8. Limit Theorems 394
  9. Additional Topics in Probability
  10. Simulation
  • Self-Test Problems and Exercises
  • Answers To Selected Problems
  • Solutions To Self-Test Problems and Exercises
  • Index


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, the Advisory Editor for International Journal of Quality Technology and Quantitative Management, and an Editorial Board Member of the Journal of Bond Trading and Management. He is a Fellow of the Institute of Mathematical Statistics and a recipient of the Humboldt US Senior Scientist Award.