University of Calgary

DATA 305 - Computational Statistical Modelling - Fall 2019

Random variables and their probability models. The Central Limit Theorem and parameter estimation. Statistical modeling of univariate and multivariate data with applications to discrete and continuous data. Data transformations. Introduction to simulation based inference including randomization and permutation tests.
This course may not be repeated for credit.

Hours

  • H(3-2)

Prerequisite(s)

  • Data Science 201 or Science 201; one of Data Science 211, Computer Science 217, 231 or 235; and one of Statistics 205, 217, 327, Biology 315, Economics 395, Political Science 399, Psychology 300, Sociology 311, Engineering 319 or Linguistics 560.

Antirequisite(s)

  • Credit for Data Science 305 and any one of Statistics 323, Psychology 301 or Sociology 315 will not be allowed.
Syllabus

Sections

This course will be offered next in Winter 2021.
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