Checking date: 30/04/2020


Course: 2019/2020

Quantitative social research methods
(13012)
Dual Bachelor in Political Science and Sociology (2009 Study Plan) (Plan: 192 - Estudio: 247)


Coordinating teacher: TORRE FERNANDEZ, MARGARITA

Department assigned to the subject: Social Sciences Department

Type: Compulsory
ECTS Credits: 6.0 ECTS

Course:
Semester:




Requirements (Subjects that are assumed to be known)
Basic knowledge of statistics
At the end of the course, students must be proficient in the following tasks: 1) operationalization of research hypotheses 2) handling and preparation of data 3) use of the main quantitative techniques in social research: a. Selecting the most appropriate technique for each type of research question and data b. Data Analysis c. Interpretation of the analyses 4) a working knowledge of Stata/R and basic programming skills
Description of contents: programme
Quantitative research techniques are a key element in the training of future professionals. This course delves into the learning of quantitative social research techniques from an applied perspective. All topics will be approached in a theoretical/practical way, using the statistical package Stata. The course is structured as follows: 1. Introduction to quantitative social research 2. Descriptive Analysis 3. Bivariate analysis 4. Multivariate Analysis: a. Linear Regression b. Logistic Regression 5. VisualizaciĆ³n and reporting
Learning activities and methodology
Master Classes (3 ECTS credits): Lecture on the theoretical content of the subject. Reduce Classes (3 ECTS credits): Practical classes in the computer room using Stata
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40

Basic Bibliography
  • Cameron, Colin A. & Pravin K. Trivedi. Microeconometrics using Stata. Stata Press. 2010
  • Long, Scott J. & Jeremy Freese. Regression Models for Categorical Dependent Variables Using Stata. Stata Press. 2014
Additional Bibliography
  • James, Gareth, Daniel Witten, Trevor Hastie, & Robert Tibshirani. An introduction to Statistical Learning with applications in R. Spinger. 2013

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