The course aims to introduce graduate students in the social sciences to the formalism, terminology, and tools for statistical analysis of the main phenomena of socio-economic systems, through both a theoretical and an
applied approach. The program covers topics ranging from the presentation and explanation of the main statistical tools (descriptive statistics and exploratory data analysis) to the implementation and measurement of socioeconomic theories that influence our dynamic system (statistical inference). 
At the end of the course, the student will be able to quantify (hypothesis testing) the main socio-economic phenomena and compare the most widely used methods of measurement (inference).

- Populations and Samples
- Descriptive Statistics
- Exploratory data analysis: Cluster and Principal component analysis
- Random Variables and Probability Distributions
- Statistical Inference: Point and confidence interval estimation
- Statistical Inference: Significance Tests
All topics will also be covered from an empirical point of view using R and STATA software (datalab)

No specific prerequisites are required

At the end of the course, students will be able to manage the acquired techniques of economic statistics concerning different economic agents and sectors: consumers, firms, industry associations and governments.

Knowledge and Understanding: at the end of the semester students are expected to know statistical methods by means of which they will be able to analyze economic systems. Further, they will learn how to find information from several statistical sources and how to manage it.

Applying Knowledge and Understanding: students will be able to make inference by means of quantitative methods and to evaluate their efficacy.

Making Judgements: students will be able to analyze information to solve several types of problems, to choose the most appropriate method and to evaluate the soundness of found solutions.

Communication Skills: students will learn how to present results from their analyses by means of short reports and graphics. They will learn to work together and present their statistical analysis.

Learning Skills: students will be able to apply technical knowledge acquired in other courses and integrate them with skills that they will learn during this course.

The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it

Teaching

• Frontal lessons
• Exercises in the classroom
• Exercises at home

Innovative teaching methods

Debate: During the brainstorming phase on the assigned topic, the students are divided into teams, one for and one against. They are then tasked to participate in a debate on the key topic established in the preparatory phase.

Problem-based learning: To facilitate problem-based learning within small groups, the classroom environment will be organised to encourage collaborative work in small groups, preferably of 6-8 students.

Attendance

Attendance highly suggested

Course books

• Agresti, Alan. and B. Finlay. Statistical Methods for the Social Sciences (5th edition), Pearson Education Limited (selected chapters to be indicated)
• Casella, G. and R. Berger. Statistical Inference (2nd edition), Duxbury Advanced Series (selected chapters to be indicated)
• Lecturer's slides and teaching materials

Assessment

Written exam with theoretical questions and applied exercises on R and STATA

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.

Teaching

There are no changes in the conditions for non-attending students 

Attendance

There are no changes in the conditions for non-attending students 

Course books

There are no changes in the conditions for non-attending students 

Assessment

There are no changes in the conditions for non-attending students 

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.