Lectures. Application of the contents learned to the empirical research issues. Discussion of results.
Seminars on specific topics included in the course.
Research activity: literature research and data collection.
Data analysis laboratories with training on statistical software.
Paper presentations on the topics of the course.
1. Factorial analysis - Cluster analysis - Matching for risk analysis
2. Multiple Regression Models - Log-Linear Models - Non-linear and Logistic Regression Models - Multilevel Models - Structural Equation Models -
3. In-depth topics: software R Studio
1. Bartholomew D. J., Steele F., Moustaki I., Galbraith J. I. (2008). Analysis of Multivariate Social Science Data. Boca Raton, FL: CRC Press, Taylor & Francis, pp. 1-144; 175-208.
for Matching techniques: - https://openknowledge.worldbank.org/bitstream/handle/10986/25030/9781464807794.pdf?sequence=2&isAllowed=y
- https://www.amazon.it/Effect-Introduction-Research-Design-Causality/dp/1032125780
for software applications:
Hahs-Vaughn, D. L. (2017). Applied Multivariate Statistical Concepts. New York, NY: Routledge, pp. 1-56; 335-440
Digital manuals of the software used.
in Italian to consult, if necessary:
Gallucci M., Leone L., Berlingeri M. (2017), Modelli statistici per le scienze sociali, Pearson, Milano, pp. 323-406 (analisi fattoriale).
Fabbris L. (1997), Statistica multivariata. Analisi esplorativa dei dati, McGraw-Hill, Milano, pp. 3-77; 301-351 (analisi dei gruppi).
2. Bartholomew D. J., Steele F., Moustaki I., Galbraith J. I., Moustaki I.. (2008). Analysis of Multivariate Social Science Data. Boca Raton, FL: CRC Press, Taylor & Francis, pp. 145-174; 289-362.
for software applications:
Hahs-Vaughn, D. L. (2017). Applied Multivariate Statistical Concepts. New York, NY: Routledge, pp. 57-272; 441-570.
Digital manuals of the software used.
in Italian to consult if necessary:
Bohrnstedt G. W. and Knoke D. (1998), Statistica per le scienze sociali, Il Mulino, Bologna, pp. 207-375 (non-linear regression models and logistics).
Gallucci M., Leone L., Berlingeri M. (2017), Modelli statistici per le scienze sociali, Pearson, Milano, pp. 41-98 (multiple regression models).
3. In-depth topics:
James Lang & Paul Teetor, R Cookbook, 2nd Edition (https://www.tidytextmining.com/)
http://www.sthda.com/english/ https://app.rawgraphs.io/
Subjects | Text References | |
---|---|---|
1 | 1. Clustering Analysis - Matching for Risk Analysis - Factorial Analysis Lectures, data collection from official sources, spreadsheet exercises, and applications | Bartholomew D. J., Steele F., Moustaki I., Galbraith J. I. (2008). Analysis of Multivariate Social Science Data. Boca Raton, FL: CRC Press, Taylor & Francis, pp. pp. 1-144; 175. |
2 | 1a. Data processing softwares | Hahs-Vaughn, D. L. (2017). Applied Multivariate Statistical Concepts. New York, NY: Routledge, pp. 1-56; 335-440 |
3 | 2. Models of multiple regression - Nonlinear and logistic regression models - Structural equation models - Multilevel models | Bartholomew D. J., Steele F., Moustaki I., Galbraith J. I. (2008). Analysis of Multivariate Social Science Data. Boca Raton, FL: CRC Press, Taylor & Francis, pp. 145-174; 289-362. |
4 | 2a. Data processing softwares | Hahs-Vaughn, D. L. (2017). Applied Multivariate Statistical Concepts. New York, NY: Routledge, pp. 57-272; 441-570. |
5 | 3. R Studio for data analysis - Scraping tecniques | James Lang & Paul Teetor, R Cookbook, 2nd Edition (https://rc2e.com/) Julia SIlge & David Robinson, Text Mining with R: a Tidy Approach (https://www.tidytextmining.com/). |
6 | 3a. R Studio tools | https://sicss.io/boot_camp; https://www.sthda.com/english/; https://www.r-graph-gallery.com/index.html https://app.rawgraphs.io/; https://corplingstats.wordpress.com/. |