DANA 4810: Predictive Analytics - Quantitative Data

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Course Format Lecture 3.0 h + Seminar 0.0 h + Lab. 1.0 h
Credits 3.0

Course Description

Predictive analytics is a process of using and applying statistical analysis techniques for estimation and forecasting. Students learn standard methodology for analyzing quantitative data, including analysis of variance, design of experiments, simple regression, multiple regression, data transformation, and generalized linear models.

Registration in this course is restricted to students admitted to the Post-Degree Diploma in Data Analytics and Post-Degree Certificate in Data Analytics.

Prerequisite(s): A passing mark from Data Analytics Math Assessment Test or an "S" grade in MATH 4801; and a minimum "C" grade in DANA 4800.

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