ANALYSIS OF QUESTIONNAIRE DATA

The course aims at introducing the methodology and practical techniques for the design of questionnaires and statistical data analysis of survey data. This knowledge is relevant in all areas where phenomena need to be analyzed on the basis of collected data.

1. Knowledge and understanding (Conoscenza e capacità di comprensione). The course will give the main concepts and techniques for the design of questionnaires and data analysis of collected data. On completion, students will acquire knowledge about: i) design of a statistical survey; ii) techniques for questionnaire design; iii) methods for statistical analysis of collected data and for providing statistical reports.
2. Applying knowledge and understanding (Capacità di applicare conoscenza e comprensione). On completion, students will be able: i) to design a statistical survey; ii) to analyze collected data through suitable statistical methods and models; iii) to provide a statistical report for summarizing the main results.
3. Making judgements (Autonomia di giudizio). On completion, students will able how to choose a suitable statistical model, apply sound statistical methods, and perform the analyses using statistical software R and/or SAS.
4. Communication skills (Abilità comunicative). On completion, students will be able how to present the results from the statistical analyses through suitable reports, and which conclusions can be drawn from the analyses.
5. Learning skills (Capacità di apprendimento). On completion, students will learn the main statistical techniques for the analysis of questionnaire data and use software like R and/or SAS to carry out data analysis and data modeling .

Lectures and practical data modeling in R or SAS.

Methods of Data Collection. Introduction to Survey Research Methods. Component of Surveys. Survey Delivery Approaches. Sampling Techniques.

Design of Questionnaires. Define research aims. Identify the population and sample. Designing Questions. Types of measures and Questions. Types of error in surveys. Evaluating survey questions.

Preparing Survey Data for Analysis. Formatting a Data File. Coding and Data Entry. Data Cleaning. Lab in R and/or in SAS.

Statistical Analyses of Questionnaire Data. Description of responses. Description of Relationships between variables. Latent Class Analysis. Item Response Theory. Lab in R and/or in SAS.

Falissard B. (2012), Analysis of Questionnaire Data with R, CRC Press, Boca Raton

Bartolucci F., Bacci S., Gnaldi M. (2016), Statistical Analysis of Questionnaires, CRC Press, Boca Raton

Fowler F. J. (2009), Survey Research Methods, SAGE Publications, Thousand Oaks, California

Lecture notes and slides