Concept

Statistique mathématique

Cours associés (32)

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PHYS-216: Mathematical methods (for SPH)

Ce cours est un complément aux cours d'analyse et d'algèbre linéaire qui apporte des méthodes et des techniques mathématiques supplémentaires requises pour les cours de physique de 3e année, notamment

CS-552: Modern natural language processing

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BIO-449: Understanding statistics and experimental design

This course is neither an introduction to the mathematics of statistics nor an introduction to a statistics program such as R. The aim of the course is to understand statistics from its experimental d

CIVIL-606: Inference for large-scale time series with application to sensor fusion

Large-scale time series analysis is performed by a new statistical tool that is superior to other estimators of complex state-space models. The identified stochastic dependences can be used for sensor

MATH-655: Advanced methods for causal inference

This course covers recent methodology for causal inference in settings with time-varying exposures (longitudinal data) and causally connected units (interference). We will consider theory for identifi

MATH-517: Statistical computation and visualisation

The course will provide the opportunity to tackle real world problems requiring advanced computational skills and visualisation techniques to complement statistical thinking. Students will practice pr

MATH-441: Robust and nonparametric statistics

In the decades from 1930 to 1950, many rank-based statistics were introduced. These methods were received with much interest, because they worked under weak conditions. Starting in the late 1950, a th

ENV-400: Air pollution and climate change

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EE-605: Statistical Sequence Processing

This course discusses advanced methods extensively used for the processing, prediction, and classification of temporal (multi-dimensional and multi-channel) sequences. In this context, it also describ

MATH-455: Combinatorial statistics

The class will cover statistical models and statistical learning problems involving discrete structures. It starts with an overview of basic random graphs and discrete probability results. It then cov