Checking date: 16/05/2022

Course: 2022/2023

Statistics for social sciences III
Study: Bachelor in Sociology (208)

Coordinating teacher: KAISER REMIRO, REGINA

Department assigned to the subject: Statistics Department

Type: Electives
ECTS Credits: 6.0 ECTS


Requirements (Subjects that are assumed to be known)
Estadistica Aplicada a las CCSS 2
Forecasting Time Serires with ARIMA Models Logit
Skills and learning outcomes
Description of contents: programme
1. Time Series. Forecasting with ARIMA models Characteristics of a time series: Frequency, trend and seasonal cycle. Concept of a stationary time series ACF an PACF White noise Autoregressive models AR (p) Moving average models MA (q) ARMA and ARIMA models Estimation and diagnosis. Forecasting Seasonal ARIMA models : identification, diagnosis and prediction. 2. Logistic regression. Logit Model Overview. Parameter estimation. Interpretation of the parameters. Model diagnose 3. Extensions
Learning activities and methodology
Theory (4ECTS). Lectures with support material available via web. Practices (2ECTS) Classes in computer classroom. Debates.
Assessment System
  • % end-of-term-examination 50
  • % of continuous assessment (assigments, laboratory, practicals...) 50
Calendar of Continuous assessment
Basic Bibliography
  • Peña, D. Análisis de Series temporales. Alianza. 2005

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