79215 - Planning and Design of Economic Surveys

Learning outcomes

At the end of the course the student has skills on complex sampling plans. In particular, the student is able to: - design complex sample surveys - analyze and synthesize the information obtained in an advanced statistical perspective - identify and use the appropriate estimators for the inferential problem to be faced - evaluate and communicate the degree of uncertainty of the estimates obtained .

Course contents

MODULE 1 (Marketing and Market Research curriculum students only)


FIRST PART


The design of a statistical survey
Sampling surveys: recalls of the main aspects of sampling from finite populations
The survey tool: the questionnaire. Structure, typology and formulation of the questions. Methods of administering the questionnaire. Evaluation of the validity of the questionnaire: tools for the reliability analysis




SECOND PART


Latent variable models for categorical data


Item Response Theory models for binary and ordinal data
The multidimensional case




MODULE 2 (students in the Marketing and Market Research curriculum and Quantitative Methods for Economic Decisions curriculum teaching mutuation 79215 - DESIGN AND IMPLEMENTATION OF ECONOMIC INVESTIGATIONS)


PART THREE
Latent variable models for continuos data: the factorial analysis

Latent variable models for classification: the latent class analysis

Models for hierarchical data: Multilevel regression models

 

The course includes laboratory exercises using the R software


Some case studies relating to socio-behavioral and economic investigations will also be discussed in the classroom with experts

Readings/Bibliography

• G. Cichitelli, A. Herzel, G.E. Montanari, Il campionamento statistico, Il Mulino
• David J. Bartholomew ...[et al.], The analysis and interpretation of multivariate data for social scientists, 2002, Chapman & Hall
• Basics of Item Response Theory (by Frank Baker) - EdRes.org (on-line)

Teaching methods

The course consists of lectures and computer laboratory activities in  R: lectures deal with methodological issues about the statistical tools listed in the course content, while computer laboratory sessions focus on the application of  on specific case studies.

Assessment methods

There is a partial test at the end of the first lesson period on module 1 and a test at the completion of the course

The final grade will be the average of the two tests. The assessment is aimed at determining whether the methodological tools have been acquired to face a statistical analysis in the various phases, also with the aid of an adequate IT tool. The test (partial or total) is written and includes open and multiple choice questions both on methodological content and commentary on R.

Teaching tools

Slides, data sets and reports on statistical surveys

Office hours

See the website of Stefania Mignani