Short syllabus

Objectives

The goal of Stats 67 is to provide the basic probability and inference concepts required to model and estimate uncertainty. Specific course objectives are:

• to introduce the fundamental principles of probability theory, probability distributions, and inferential statistics;

• to illustrate, when possible, how probability and statistics are applied to practical problems in ICS;

• to provide a solid foundation for future class work.

Topics covered

Probability

• Simple and conditional probabilities

• Counting (permutations, combinations)

• Discrete random variables (binomial, Poisson)

• Continuous random variables (normal, exponential)

• Joint probability distributions

Statistical inference

• Sampling and sampling distributions

• Estimation with confidence intervals

• Tests of hypotheses (1 sample, 2 samples)

• Simple linear regression

Class organization (traditional lecture format)

Lectures present the core material of this class, illustrated with examples. You are strongly encouraged to check the corresponding chapter section(s) out of the textbook BEFORE attending lectures. This greatly enhances the learning process. Lecture topics and corresponding book chapters are posted weekly on the Lectures page. 

Discussion sections provide an opportunity to practice exercises and ask questions. Attendance is not mandatory but it is recorded and earns participation points for active work. Details of participation credit is provided in the Grades section of the syllabus specific to your quarter.