Applied Statistics

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Program Overview

The Master's program in Applied Statistics aims to train specialists capable of analyzing and interpreting data in various fields such as healthcare, economics, environment, and engineering. It combines theoretical courses in statistics, probability, and machine learning with practical applications through case studies and projects. Emphasis is placed on the use of specialized software such as R, Python, and SAS for data processing and modeling.

Teaching Language : Frensh

Curriculum Highlights

Core Courses

·        Probability and Inferential Statistics

·        Linear Models and Regression

·        Data Analysis

·        Time Series and Forecasting

·        Classification and Clustering Methods

·        Statistical Programming (Python, R, SAS)

Advanced Topics

·        Machine Learning and Applied Artificial Intelligence

·        Bayesian Analysis and Inference

·        Spatial Statistics and Geostatistics

·        Epidemiology and Biostatistics

·        Survival Analysis and Risk Models

·        Standardization and Data Adjustment Methods

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Admissions Information

Required diploma: Bachelor's degree in Mathematics, Probability and Statistics


Notes:



Admission depends on the number of teaching places available.



Selection is based on applicants' ranking.

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