Introduction to empirical social research. Design and implementation of a sample survey. Methods of data collection, questionnaire construction and measurement scales. Descriptive statistics and graphical representations. Practical examples and applications in excel. Basic concepts of text analysis and cluster analysis.
To know the basic concepts of descriptive statistics, to read and interpret a statistical report, a graph, a summary statistic or an indicator, and also a simple statistical model. To be able to do empirical social research. To be able to develop a sample survey and to implement a questionnaire for data collection. To be able to provide a synthetic description of data through quantitative analyses, by correctly interpreting the studied phenomena, supported by the use of Excel for creating graphs and computing summary statistics.
Prerequisiti
Basic knowledge of mathematics.
Metodi Didattici
Face-to-face lectures, exercises, data labs, webinars, project works.
Altre Informazioni
None
Modalità di verifica apprendimento
Written exam, which consists of a series of eight questions (open questions or brief exercises), which require a brief answer concerning the arguments of the course, or the construction or interpretation of graphs and tables.
In addition - but not compulsory - students' group mini-project about the analysis of a dataset given by the teacher. The mini-project will be developed during several lessons throughout the course and with some work outside class. At the end of the course, each group (formed by 1-3 students) will do a Powerpoint presentation: each student must present part of the slides, for an overall duration of 15 minutes. Evaluation: 0-3 points to be added to the final mark of the written exam.
Programma del corso
Introduction to empirical social research. Design and implementation of a sample survey. Types of sampling methods: characteristics and differences. Methods of data collection (face-to-face, telephone, on-line survey): characteristics and differences. The questionnaire: characteristics of the questionnaire and methods for its construction. Measurement scales. Descriptive statistics: frequency tables, central tendency and variability measures, graphical representations, bivariate frequency tables, correlation, simple and multiple least square regression line. Practical examples and applications in excel. Basic concepts of text analysis and cluster analysis.