Math 350: Mathematical Probability

Fall 2026

Instructor: Enrique Treviño
Lectures: MWF 1:00pm -2:20pm BR 121
Office Hours: MWF from 9:00am to 10:00am, T from 1pm to 2:30pm.
Office: Brown Hall 123
Email:
Phone Ext.: #6187

Announcements

Course Description

Discrete and continuous probability. Distributions, the law of large numbers, the central limit theorem, random variables, and generating functions. Prerequisites: Mathematics 210 and 230 or permission of the instructor.

Textbook

Introduction to Probability (2nd revised edition) by Charles M. Grinstead and J. Laurie Snell

This book and other resources are freely available online here. For a direct link to the pdf, you can click here

Topics to be covered

The following is a tentative list of topics that will be covered:

Section 1.2: Discrete Probability distributions.
Section 2.2: Continuous Density functions.
Section 3.1: Permutations
Section 3.2: Combinations
Section 4.1: Discrete conditional probability.
Section 4.2: Continuous conditional probability.
Section 6.1: Expected Value
Section 6.2: Variance of discrete random variables
Section 6.3: Continuous random variables
Section 5.1: Important distributions
Section 5.2: Important densities
Section 8.1: Law of large numbers: Discrete Random Variables
Section 8.2: Law of large numbers: Continuous Random Variables
Section 9.1: Central limit theorem: Bernoulli trials
Section 9.2: Central limit theorem: Discrete independent trials
Section 9.3: Central limit theorem: Continuous independent trials
Chapter 11: Markov chains

Student Learning Outcomes

Some main learning outcomes include:

Learn what probability is and be able to compute the probability of different types of events happening.
Learn what expected value and variance are, and be able to evaluate them.
Learn discrete and continuous distributions.
Learn what the Central Limit Theorem states, why it is useful, and why it is true.

Grading

The course grade will be based on:
Homework 10%
Midterm 1    20%,
Midterm 2    20%,
Midterm 3    20%
Final Exam 30%.

Homework

There will be written homework daily. The homework will be turned in and will reinforce the material learned in class. Collaboration in the homework is permitted, however you must write your own solutions in your own words (or symbols). You should submit your homework in class. You must also support your answers with the intermediate steps you took to reach the answer.
You can find the homework assignments for this class below:
Homework.

Exams

On the midterms and the final exam you must work on the problems on your own. No collaboration permitted in the exams. No use of electronics is allowed either. Use of a smart phone (or other smart device) during an exam will lead to an automatic zero in that exam.
The following dates are tentative:

The first midterm will be on Friday October 2.

The second midterm will be on Friday October 30.

The third midterm will be on Friday November 20.

The final exam will be a cumulative three hour exam. It will be on Wednesday December 16 from 1:30pm to 4:30pm.

Attendance

Students are expected to come to every lecture and every exam. If the dates of the exams conflict with Lake Forest approved events, inform me as soon as possible.

Description of instructional time and expectations:

This course meets 3 times per week for 4.5 hours per week. The course carries 1.0 course credit (equivalent to four semester credit hours). Students are expected to devote a minimum of 12 hours of total work per week (in-class time plus out-of-class work) to this course.

Academic Honesty

Please read the College's information on Academic Honesty. If a student cheats in an exam, quiz or homework assignment, I will proceed with charging the student with the Academic Honesty Judicial Board. The usual (first) penalty is a 0 in the assignment on which the cheating occured plus some ethics lectures the student would take. The second penalty is usually suspension.

AI policy

The core of your grade comes from handwritten tests. Any use of AI on those tests will be an automatic zero. You can use AI to help you study or help you go through the Homework. I don't recommend using it, as it can easily lead you to think you understand something you don't.

Academic Resources, Protocols, and Policies

Click here: Academic Resources, Protocols, and Policies

Last modified on August 28, 2026.