Checking date: 17/04/2024

Versión en español

Course: 2024/2025

Categorial data analysis
(13733)
Bachelor in Statistics and Business (Plan: 400 - Estudio: 203)


Coordinating teacher: GALEANO SAN MIGUEL, PEDRO

Department assigned to the subject: Statistics Department

Type: Electives
ECTS Credits: 6.0 ECTS

Course: 4º
Semester:



Requirements (Subjects that are assumed to be known)
Statistical Inference Techniques I Statistical Inference Techniques II Regression Methods
Objectives
1. Understanding the basic techniques for analyzing categorical data. 2. Knowing and managing statistical programs for the analysis of categorical data. 3. Using the methodology for the analysis of real data. 1. Capacity for analysis and synthesis. 2. Modeling and resolution of problems. 3. Oral and written communication.
Skills and learning outcomes
Link to document

Description of contents: programme
1. Introduction: Distributions and inference for categorical data. 2. Contingency tables: Description and inference. 3. Introduction to generalized linear models. 4. Logistic regression models and alternatives. 5. Models for multinomial responses. 6. Log-linear models and alternatives. 7. Models for paired samples.
Learning activities and methodology
Theory (4 ECTS). Theoretical classes with support material available on the Web. Practice (2 ECTS) Problem-solving classes and labs.
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100

Calendar of Continuous assessment


Extraordinary call: regulations
Basic Bibliography
  • Agresti, A. Categorical Data Analysis. New York: John Wiley & Sons. 2013 (third Edition)
  • Agresti, A.. An introduction to Categorical data analysis. John Wiley & Sons,. 2007
  • Andersen, E.B . Introduction to the Statistical Analysis of Categorical Data. Springer. 1997
  • Collett D. . Analysis of Binary Data. Chapman & Hall.. 2003
  • Cox D.R. & Snell E.J.. Analysis of Binary Data. Chapman & Hall. 1989
  • Cox D.R. & Snell E.J.. Analysis of Binary Data. Chapman & Hall. 2018
  • Kateri, M. Contingency Table: Analysis Methods and Implementation Using R. Birkhäuser. 2014
  • Zelterman, D. Models for Discrete Data. Oxford University Press. 2006 (revised edition)
Recursos electrónicosElectronic Resources *
Additional Bibliography
  • Bishop, Y. M., Fienberg, S. E., Holland, Paul W. . Discrete Multivariate Analysis: Theory and Practice. Springer (Originally published by MIT Press, 1975). 2007
  • Hosmer, D.W. and Lemeshow, S.. Applied Logistic regression. Willey. 2000
  • McCullagh, P. and Nelder, J.A.. Generalized Linear Models, Second Edition. London: Chapman & Hall. 1989
  • Stokes, M.E., Davis, C.S. and Koch, G.G.. Categorical Data Analysis Using The SAS System, Second Edition. NC: SAS Institute Inc.. 2000
(*) Access to some electronic resources may be restricted to members of the university community and require validation through Campus Global. If you try to connect from outside of the University you will need to set up a VPN


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