Course Topics
Module 1 • Descriptive Statistics: Frequency tables; • Summary Statistics (measures of central tendency and dispersion); • Graphical tools; • Introduction to bivariate analysis; • Probability: events, counting rules and classic definition, additive and multiplicative rule, conditional probability and independence. Module 2 • Discrete and continuous random variables, probability distributions and expected values; • Central Limit theorem and its applications; • Introduction to inferential statistics; • Sampling and sampling distributions; • Point estimators; • Confidence Intervals.

Teaching format
Frontal lectures, exercises.

Educational objectives
• Knowledge and understanding: Students learn the basics of probability and statistical theory. • Applying knowledge and understanding: Students develop the ability to analyze real data by exploiting via tables, graphical tools, and data summaries. • Making judgments: Ability to describe and discuss specific economic issues with a critical point of view by analysing data or evaluating probabilities. • Communication skills: Ability to present in a consistent and precise way the results obtained from the statistical or probabilistic analysis. • Learning skills: Ability to understand and analyse the economic data from a quantitative perspective.

Additional educational objectives and learning outcomes
Students successfully attending the course will be able to i) explore, visualize, and interpret different types of data by producing graphs and computing numerical data summaries, ii) describe empirical phenomena through probability and random variables, and use basic theorems to manipulate them.

Assessment
A final written exam with both closed and open questions.

Evaluation criteria
The test will have no negative consequences, as it is aimed at making aware students of their own knowledge. In case of “not-passed” outcome, the student could decide with the Lecturer how to improve his/her knowledge.