Studies axioms, combinatorial analysis, independence and conditional probability, discrete and absolutely continuous distributions, expectation and distribution of functions of random variables, laws of large numbers, central limit theorems, and simple Markov chains if time permits
Time: M-F 01:00PM – 02:35PM
Location: GUGG 2
Office hours: See details here
Homework: 25% – Weekly homework (you must turn them in)
Midterm I (06/10): 25%
Final (to be announced) : 30%
Other books I like
The Law of Large Numbers and the Central Limit Theorem
Uniform distribution, Exponential distribution, Memoryless distributions.
Introduction to probability distributions and binomial distribution
Introduction to Variance and Chebyshev’s inequality.
Introduction to random variables, CDF, density functions and independence for random variables
Monty Hall Dilemma, Bayes’s Formulas and Independent Events
Introduction to conditional probability theory and the multiplication rule. Use of probability in court
Sample spaces, events and probability measure.
Addition and Subtraction principles of counting. Inclusion-Exclusion formula.
Defining probability for random experiments with equally likely outcomes, and the Multiplication Principle
Comment about the course and discussion about probability of events