Checking date: 08/06/2021


Course: 2021/2022

Advanced Statistical Data Analysis
(17467)
Study: Bachelor in Management of Information and Digital Contents (340)


Coordinating teacher: MUÑOZ GARCIA, ALBERTO

Department assigned to the subject: Department of Statistics

Type: Compulsory
ECTS Credits: 6.0 ECTS

Course:
Semester:




Requirements (Subjects that are assumed to be known)
Basic multivariate analysis
Objectives
SPECIFIC SKILLS and COMPETENCES 1. To know and use advanced statistical techniques, with last generation software support. 2. To extract and analyze information from large data sets. TRANSVERSAL SKILLS and COMPETENCES 1. Ability of information analysis and synthesis. 2. Modelization and resolution of practical problems in Data Mining. 3. Oral and written communication skills.
Skills and learning outcomes
Description of contents: programme
1. R programing language 1.1 Data types and importing data 1.2 Loops and conditionals 1.3 Functions 2. Exploratory Data Analysis 2.2 Ggplot2 package 3. Supervised Classification 3.1 K-nearest neighbors 3.2 Decision Trees 3.3 The Gaussian distribution and discriminant analysis 3.4 Support Vector Machines 3.5 Logistic Regression 4. Dimensionality Reduction and clustering techniques 4.1 Principal Component Analysis 4.2 K-means 4.3 Hierarchical Clustering 5. How to write a report with R-Markdown
Learning activities and methodology
The program consists of 14 theoretical classes with supporting material available in the global classroom and 14 sessions based on computer practice sessions. Every week students will have an optional collective tutorial where they can solve their doubts.
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100
Basic Bibliography
  • Pathak, Manas A.. Beginning data science with R. Springer. 2014

The course syllabus may change due academic events or other reasons.