# 88089 - STATISTICS

### Scheda insegnamento

• Docente Silvia Bianconcini

• Crediti formativi 10

• SSD SECS-S/01

• Modalità didattica Convenzionale - Lezioni in presenza

• Lingua di insegnamento Inglese

• Materiale didattico

• Orario delle lezioni dal 23/09/2019 al 20/12/2019

### SDGs

L'insegnamento contribuisce al perseguimento degli Obiettivi di Sviluppo Sostenibile dell'Agenda 2030 dell'ONU.  ## Conoscenze e abilità da conseguire

The aim is to lead the student in learning the basic statistical notion. The first theoretical part introducing the basic statistics is followed by an application part with practical exercises.

## Programma/Contenuti

The course program is organized in three parts as described below.

Exploratory Data Analysis

The data matrix. Types of variables. Frequency tables. Graphical representations. Summary measures of position and dispersion. Association of two quantitative variables, covariance and correlation coefficient. Outline of simple linear regression.

Probability Theory

Random experiment, sample space and events, probability measure. Conditional probability, independence. Random variables. Expected value and variance of a random variable. Discrete and continuous random variables. Bernoulli and binomial distribution. Gaussian distribution.

Inferential Statistics

Random sampling. Parametric statistical models. Sampling distributions. Point estimation. Bias and mean squared error. Confidence intervals for the mean of a Gaussian population. The Student t distribution. Approximate confidence interval for a probability. Hypothesis testing on the mean of a Gaussian population. The p-value. Inference on a proportion.

## Testi/Bibliografia

Nevo D. (2017). Making sense of data through statistics: an introduction. Legerity Digital Press. Second Edition.

## Metodi didattici

Teacher's lectures and tutorials.

## Modalità di verifica dell'apprendimento

For attending students, there are 3 tests during the Statistics course, otherwise, is possible to do only one full test in the ordinary examination session.

To pass the exam the student score has to be greater than or equal to 18 in the full examination and in partial tests (for attending students) the average score has to be not less then 18.

If the student does not pass the examination in the following course session, he/she can give back it only in September session.

## Strumenti a supporto della didattica

Slides of the course, materials for self-assessment.

## Orario di ricevimento

Consulta il sito web di Silvia Bianconcini