probability-statistics and applications

Program Overview

The doctoral training in Probability-Statistics and their Applications at Mustapha Ben Boulaid University Batna 2 falls under the field of Mathematics and Computer Science, within the Applied Mathematics stream. This program, designed to last a minimum of 3 years and a maximum of 5 years, aims to train high-level researchers capable of applying advanced probabilistic and statistical methods to complex problems in strategic sectors such as public health, finance, environment, and agriculture. Supported by the research laboratory Mathematical Techniques for Applications: Deterministic and Stochastic Aspects, the program combines rigorous theoretical training with practical applications, notably in modern statistical analysis, censored data modeling, and financial time series.

Teaching Language : French, English

Curriculum Highlights

Core Courses

The knowledge enhancement program includes core courses taught over two semesters, with 2 hours per week per course. These courses are designed to consolidate foundational knowledge in probability and statistics and prepare doctoral students for research.

Semester 1:

Statistical Analysis of Censored Data (26 hours): Introduction to methods for handling incomplete data, such as the Kaplan-Meier estimator.
Modeling Volatility in Time Series (26 hours): Foundations of econometric models like GARCH for financial data analysis.
Statistical Learning for Data Science 1 (26 hours): Introduction to statistical learning techniques for big data analysis.

Semester 2:

Regression Models and Statistics for Functional Data (26 hours): Basics of semi-parametric regression for functional data.
Extreme Value Statistics (26 hours): Introduction to modeling rare events, such as extreme weather phenomena.
Statistical Learning for Data Science 2 (26 hours): Advanced statistical learning methods.

Supplementary Courses (each semester):

Research Methodology (26 hours/semester): Scientific writing and research project design.
Introduction to Didactics and Pedagogy (26 hours/semester): Preparation for university teaching.
Information and Communication Technologies (ICT) (26 hours/semester): Programming skills and digital tools.
Language Skills Development (26 hours/semester): Scientific English for publishing and international communication.

Advanced Topics

Proposed thesis topics reflect advanced and applied themes:

ü Nonparametric Estimation for Censored Data (Merahi Fateh): Study of survival and hazard functions for biomedical and reliability applications.

ü Semi-parametric Estimation of the Regression Function for Functional Data (Merahi Fateh): Analysis of curve-shaped data, with applications in meteorology, finance, and medicine.

ü Cluster Identification in Datasets Using Pseudo-Polygon-based Methods (Merahi Fateh): Innovative methods for analyzing and visualizing complex data.

ü Modeling and Forecasting Financial Time Series Volatility (Hadjira Abdelmounaim): Use of GARCH models and machine learning in finance.

ü Big Data Analytics for Disease Prevention and Detection (Boussaid Samira): Analysis of medical data for early disease prevention and detection.

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Admissions Information

Applicants must hold a master’s degree in applied mathematics or an equivalent foreign qualification.

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