The course introduces students to the statistical aspects of the design and analysis of sample surveys. Particular emphasis is given on data quality issues and statistical methods to deal with qualitative data.
Having successfully completed the course students will be able to:
- demonstrate knowledge and understanding of the basic principles underlying survey design and the methods for designing and selecting a sample from a population
1. (Knowledge and understanding) understand the different approaches to data collection; know the sources of error in survey processes and basic ideas on statistical modelling for categorical data
2. (Applying knowledge and understanding) analyze survey results and specify a statistical model for qualitative data
3. (Making judgements) evaluate data source characteristics and data quality in different contexts
4. (Communication skills) effectively communicate orally and in writing characteristics of data source and statistical model results
5. (Learning skills) demonstrate the ability to apply the knowledge, skills and the minimum competencies described in the Syllabus

Statistical inference (compulsory)

1. Statistical survey design.
- Data collection methods. Interviewing techniques.
- Questionnaire design.
- Non-sampling errors in survey.
- Sampling techniques.
2. Undesigned data sources: administrative data, privately held data, big data.
3. Statistical associations with qualitative data. Statistical modeling for categorical data

Basic textbooks:
Statistics Canada, Survey Methods and Practices,https://www150.statcan.gc.ca/n1/pub/12-587-x/12-587-x2003001-eng.pdf

G. Brancato, A. Boggia, G. Ascari (2018) Linee Guida per la Qualità delle Statistiche del Sistema Statistico Nazionale, ver. 1.0, Istat, (except topics H, I, J, K, L M in Part II), https://www.istat.it/it/files/2018/08/Linee-Guida-2.5-agosto-2018.pdf

suggested textbook (point 3): Bilder C.R., Loughin T.M. (2014) Analysis of Categorical Data with R, CRC Press, Taylor & Francis Group.

Additional bibliographical and lecture materials will be available on Moodle2.

Lectures. Individual homework and team work

The lecture materials (slides) will be available on Moodle2.

Verification of learning takes place at different times and in several ways:

- attending students
1. During the course, homework will be assigned to be delivered within established deadlines
2. classroom tests will be carried out during the course
3. presentation of a report on the results of a project (individual or group) assigned at the end of the course

The final evaluation will take place by averaging the marks obtained in the 3 parts (with weights respectively equal to 0.1, 0.5, 0.4).
The set of tests is such that it is possible to judge the achievement of the training objectives as set out above.
Verification of learning takes place at different times and in several ways:

- attending students
1. During the course, homework will be assigned to be delivered within established deadlines
2. classroom tests will be carried out during the course
3. presentation of a report on the results of a project (individual or group) assigned at the end of the course

The final evaluation will take place by averaging the marks obtained in the 3 parts (with weights respectively equal to 0.1, 0.5, 0.4).
The set of tests is such that it is possible to judge the achievement of the training objectives as set out above.
Verification of learning takes place at different times and in several ways:

- attending students:
1. During the course, homework will be assigned to be delivered within established deadlines
2. classroom tests will be carried out during the course
3. presentation of a report on the results of a project (individual or group) assigned at the end of the course

The final evaluation will take place by averaging the marks (on a scale of 18-30 points) obtained in the 3 parts (with weights equal to 0.1, 0.5, and 0.4, respectively).
The set of tests is such that it is possible to judge the achievement of the training objectives as set out above.

- non-attending students: written exam in which theoretical aspects and the solution of exercises will be requested on the course topics. The written exam consists of at least 5 questions. To obtain the minimum passing grade (18/30), students must provide sufficient answers to at least 3 questions.

Online registration for the exam is mandatory and will be closed 3 days before the due date.

The course deals with topics related to United Nations 2030 Agenda SDGs (3, 5, 10).