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Statistical Methods for Data Analysis - Period 1 Course Overview
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Computer Sciences
Instruction in: English
Course Code: XB_0172
Transcript Source: Partner Institution
Course Details: Level 200
Recommended Semester Credits: 3
Contact Hours: 84
Prerequisites: Basic knowledge of probability is recommended but not required, as essential probability topics will be reviewed during the course.
DESCRIPTION
This course introduces the foundational concepts and techniques of applied statistics, focusing on reproducible data analysis using R. Students will gain hands-on experience in performing and interpreting statistical analyses. Topics covered include stochastic variables, probability distributions, estimators, sample distributions, confidence intervals, hypothesis testing, linear models, and logistic regression. The course is designed to lay the statistical groundwork necessary for advanced modules in “Predictive analytics and machine learning” and “Optimization and artificial intelligence”. Students will also develop the ability to critically interpret statistical outputs, an essential skill for real-world data analysis.
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