Checking date: 30/04/2020

Course: 2019/2020

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

Coordinating teacher: MOLINA PERALTA, ISABEL

Department assigned to the subject: Department of Statistics

Type: Electives
ECTS Credits: 6.0 ECTS


Students are expected to have completed
Estadistica Aplicada a las CCSS 2
Competences and skills that will be acquired and learning results. Further information on this link
Forecasting Time Serires with ARIMA Models Logit
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
Basic Bibliography
  • Peña, D. Análisis de Series temporales. Alianza. 2005

The course syllabus and the academic weekly planning may change due academic events or other reasons.