Study plan Bachelor's Degree in Applied Statistics

Study guides

The information currently available corresponds to the subjects offered during the 2023/24 academic year. If you wish to consult the information included in a study guide not found on the list, please visit the Digital Repository of Documents. The complete information of all the subjects of the Degree can be consulted in the Study Plan and timetables section.

The information on the languages used in each subject can be found in the study guide for each subject.

1st year

 104844 - Calculus 1

 104845 - Calculus 2

 104851 - Data Retreival and Storage

 104853 - Exploratory Data Analysis

 104849 - Informatics Tools for Statistics

 104846 - Introduction to Probability

 104850 - Introduction to Programming

 104843 - Linear Algebra

 104847 - Probability

 104855 - Statistical Inference 1

2nd year

 104848 - Numerical Methods and Optimisation

 104872 - Bioinformatics

 104862 - Experimental Design

 104860 - Linear Models 1

 104857 - Multidimensional Distributions

 104854 - Sampling and Survey Design

 104856 - Statistical Inference 2

 104859 - Stochastic Processes

 104867 - Survival Analysis

 104869 - Unsupervised Learning

3rd year

 104865 - Advanced Modelling

 104858 - Bayesian Methods

 104864 - Complex Data Modelling

 104861 - Linear Models 2

 104870 - Machine Learning 1

 104871 - Machine Learning 2

 104868 - Simulation and Resampling

 104873 - Statistics in the Health Sciences

 104863 - Time Series

4th year

 103166 - Bachelor's Degree Final Project

Optional

 104886 - Big Data Analysis in Bioinformatics

 104878 - Cross-Sectional Data Analysis

 104885 - Decision Theory

 104875 - Introduction to Financial Engineering

 104879 - Longitudinal Data Analysis

 104866 - Methodological Advances

 104881 - Statistics and Psychometric Models

 104877 - Statistics Consultancy

 104891 - Work Placement: Advisor Modality

 104890 - Work Placement: Analyst Modality