Study plan Bachelor's Degree in Applied Statistics

Study guides

Title of qualification awarded

Degree in Applied Statistics

Timetables

TIMETABLE

Table of credits for each course

	Basic training	Compulsory	Optional	Bachelor's Degree Final Project
1st year	54	6
2nd year	6	54
3rd year		60
4th year			48	12
Totals	60	120	48	12

Period of study

Annual registration. Courses scheduled by semester.

Part-time or full-time

Possibility of taking the slow track option (part-time studies): 30 credits in the first year and from 24 to 42 in the remaining years.

Basic and compulsory training

1st year	2nd year
1st semester - Calculus 1 - Linear Algebra - Introduction to Probability - Computer Tools for Statistics - Exploratory Data Analysis 2nd semester - Calculus 2 - Probability - Introduction to Programming - Data Retreival and Storage - Statistical Inference 1	1st semester - Multidimensional Distributions - Sampling and Survey Design - Statistical Inference 2 - Numerical Methods and Optimisation - Linear Models 1 2nd semester - Experimental Designs - Bioinformatics - Stochastic Processes - Survival Analysis - Unsupervised Learning
3rd year	4th year
1st semester - Bayesian Methods - Machine Learning 1 - Time Series - Linear Models 2 - Statistics in the Health Sciences 2nd semester - Complex Data Modelling - Advanced Modelling - Simulation and Resampling - Introduction to Econometrics - Machine Learning 2	- Bachelor's Degree Final Project

Optional subjects

 

4th year

- External Work Placement in Assistant Mode (*) - External Work Placement in Analyst Mode / 12 cr. (*) - External Work Placement in Consultant Mode / 18 cr. (*) - Methodological Advances - Advanced R

(*) You can only enrol in one of these three external work placement subjects.

In order to earn a specialisation you must complete a minimum of 30 credits belonging to that track..

Specialisation in Statistics for Health Sciences	Specialisation in Statistics for Social Sciences
- Disseny d'Assaigs Clínics - Statistics Consultancy - Cross-Sectional Data Analysis - Longitudinal Data Analysis - Statistics and Psychometric Models - Psychometrics - Topics in Bioscience and Science - Data Sources - Big Data Analysis in Bioinformatics - Public Health	- Statistics Consultancy - Econometric Models - Data Sources - Statistics and Psychometric Models - Introduction to Financial Engineering - Advanced Financial Engineering - Decision Theory - Psychometrics

All optional subjects are worth 6 credits except when specified.