STAT 355 - Introduction to Probability and Statistics for Scientists and Engineers (4)

This course is an introduction to probability, statistics and statistical computation for students who have knowledge of univariate calculus. Topics include set-theoretic and axiomatic introduction to probability; sample space; events; conditional probability; Bayes theorem; random variables; cumulative distribution functions; probability density functions; probability mass functions; moments and their properties including discussions on mean, variance and the moment generating function; standard univariate distributions such as the Bernoulli, Binomial, Poisson, Exponential; Gamma and Normal and their properties; the Central Limit Theorem (without proof) and its properties and use in statistics; introduction to the concept of randomness in observed data, estimation of unknown parameters, statistical inference and uncertainty quantification; estimation and inference in one and two sample means, proportions; contingency tables and tests for independence of row and column and equality of proportions; introduction to simple linear regression with estimation, inference, analysis of variance, plots and diagnostics. Statistical software like R or Python for estimation, inference and other statistical tasks will be used.

Grading: Graded/Satisfactory Unsatisfactory/Audit
Course ID: 57054
Consent: No Special Consent Required
Components: Discussion, Lecture
Course Equivalents: STAT 355H
Attributes: Mathematics (GFR)
Prerequisite: MATH 152 with a grade of ‘C’ or better.