A First Course in Probability

When compared to the other texts being used by other professors teaching the same course, I found this book to be very complete, and easily understandable. It is an appropriate source for learning basic probability theory and calculation. Included are many examples to solidify concepts. For the more advanced student, there are theories and proofs, and for the beginning student there are sufficient basic calculation problems to solidify the concepts. I personally liked that this text was geared towards basic mathematical theory. Other texts might include more complex probability models the business student could use to plug and play without considering the math behind the models. But if you are interested in the math. This is a great text.

Contrary to its title, this book has helped me through several probability courses. I used this book not only to study for the first actuary exam, but also as a supplement for my intermediate and doctoral-level probability/inference courses. Ross fills in gaps left by texts such as Rice, Cassella and Berger, etc., by spelling out properties of various distributions, and showing how they relate to eachother, and by doing many many examples. Incidentally, save yourself the money and get an earlier edition. I have the fifth edition, which was not even the current edition at the time that I bought it, and it's perfect as is.

A First Course in Probability by Sheldon Ross covers all the main topics of probability theory: Combinatorics, Probability Axioms, Conditional Probability and Independence, Discrete Random Variables, Continuous Random Variables, Joint Distributions, Expectation, and Limit Theorems. He develops each topic thoroughly using the definition-theorem-proof approach of classical mathematics, interspersed with numerous examples, many of which are classics in probability. This book does require a solid foundation in calculus. Consequently, it is an appropriate text for a course at an advanced undergraduate level or even a first year graduate course (which is where I first encountered it). It does not require any knowledge of truly advanced mathematics (i.e., measure theory) which one would expect to find in an upper level graduate text, such as Patrick Billingsley's Probability and Measure. Advice to students (and teachers): A student who does not have a solid foundation in calculus, as evidenced by the ability to apply integration by parts, and perhaps a year of post-calculus math which introduced the concept of the mathematical proof, will have a difficult time with this book. This book provided me with all the probability theory I needed to complete a master's degree in statistics. Since statistics is nothing more than a collection of applied problems that can be solved, modeled, or at least understood by using the tools of probability theory, I was able to coast through the rest of my master's program and didn't have to start really working again until I subsequently encountered Billingsley's book (cited above). Thank you, Professor Ross.

This book is a great introductory course in probability. The book contains various examples of everyday situations in which probability is an important factor. This book also has many practice problems, as well as the solutions. This book is a must for students of mathematics and students pursuing a career in actuary science.

Don't relate to previous reviewers' problems with this book: CLEAR though concise presentation of material, interesting examples. MOst of all: there is almost no hand-waiving in this book (it does occur somehwat in the discussion of limit theorems most memorably), that is, everything is proven. If your math level is up to par (good calculus foundation) then this is the best book for introductory (non-measure theory) prob. that I know of.