University of Calgary

DATA 305 - Computational Statistical Modelling - Winter 2022

Random variables and their probability models. The Central Limit Theorem and parameter estimation. Statistical modelling 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; and 3 units from Data Science 211, Computer Science 217, 231 or 235; and 3 units from Statistics 205, 217, 327, Biology 315, Economics 395, Political Science 399, Psychology 300, Sociology 311, Engineering 319, Digital Engineering 319 or Linguistics 560.

Antirequisite(s)

  • Credit for Data Science 305 and Statistics 323 will not be allowed.

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