00914 - Statistics

Course Unit Page

Academic Year 2018/2019

Learning outcomes

At the end of the course the students know fundamental concepts of statistics useful for the analysis of simple datasets. In particular, students - are able to apply descriptive tools for data analysis; - are aware of the basic concepts of probability; - know the fundamental of statistical inference, hence can compute relevant summaries from the data and quantify the associated uncertainty. Pre-knowledge of mathematics is required.

Course contents


Types of variables. Statistical units, population and sample. Data collection and organization. Data matrices and frequency distributions. Graphical representations. Mean values: mode, median, quartiles, arithmetic mean. Statistical indices. Main variability measures and concentration. Introduction to bivariate analysis. The relationship among two variables: association. The relationship among two variables: covariance and linear correlation. The simple linear regression.



PROBABILITY: random events and sample space. Axioms of probability. Conditional probability. Density and probability fuctions of a random variable; expectaed value and variance of a random variable. Bernoulli and Binomial distributions. Normal and Normal Standard distribution. Central limit theorem.

STATISTICAL INFERENCE: sample variability of an estimator; the sample mean estimator and its properties, point estimation and confidence intervals; statistical tests; basics on inference in regression models.


S. Borra, A. Di Ciaccio. Statistica – metodologie per le scienze economiche e sociali, terza edizione, McGraw-Hill, Milano, 2014.

Teaching methods

Frontal lectures based mostly on slides. Lectures will be on methods and practicals (tutorials sessions with excersises on blackboard).

Assessment methods

Written examination consisting in exercises, multiple-choice items and open-ended items. During written examinations, students have the possibility to bring a self-written formulary.

The examination rules apply for both students attending and not attending classes.

Teaching tools

Lessons, exercises.

Office hours

See the website of Fedele Pasquale Greco

See the website of Mariagiulia Matteucci