Data Modelling I
Introduction to formulating statistical problems and analyzing data using open-source software. Graphical and numerical descriptives. combinatorial formulae, Bayes' Theorem, probability, Discrete and continuous distributions, means and variances. Point and interval estimates, and hypothesis tests for one- and two-samples using Central Limit Theorem, and permutation tests.
Prerequisites & course information
Precludes additional credit for BIT 2000 , BIT 2009 , BIT 2100 (no longer offered), BIT 2300 (no longer offered), ECON 2201 (no longer offered), ECON 2210 , ENST 2006 , GEOG 2006 , STAT 2507 , STAT 2601 , STAT 2606 (no longer offered), and STAT 3502 . May not be counted for credit in any program if taken after successful completion of STAT 2655 . Prerequisite(s): An Ontario Grade 12 university-preparation Mathematics or equivalent, or permission of the Institute for Data Science. Lectures three hours a week, laboratory one hour a week.
Sources
- Course catalogue ↗2026–2027
- Data Modelling I ↗2026