STAT 205

STAT 205 (3) Introduction to Mathematical Statistics Sampling distribution theory. Likelihood. Parameter estimation. Confidence intervals and hypothesis testing; simple regression, analysis of variance and contingency table analysis. Credit will be granted for only one of STAT 205 or STAT 230. [3-0-0] Prerequisite: STAT 203. Please be aware that the STAT 203 and STAT 205 series is designed for students pursuing majors in Data Science, Mathematics, and Statistics. If your major falls under a different discipline, kindly refer to the Academic Calendar or reach out to an Academic or Program Advisor for guidance on selecting the most suitable Introductory Statistics/Probability courses.

DATA 101

DATA 101 (3) Making Predictions with Data Introduction to the techniques and software for handling real-world data. Topics include data cleaning, visualization, simulation, basic modelling, and prediction making. [3-1-0]

Data 311

Regression, classification, resampling, model selection and validation, fundamental properties of matrices, dimension reduction, tree-based methods, unsupervised learning.

Stat 230

Applied statistics for students with a first-year calculus background. Estimation and testing of hypotheses, problem formulation, models and basic methods in analysis of variance, linear regression, and non-parametrics. Descriptive statistics and probability are presented as a basis for such procedures.