47732 - STATISTICS

Conoscenze e abilità da conseguire

By the end of this course students are able to: - analyze a dataset using numerical indexes and graphical representations; - apply basic tools of probability theory; - produce estimates of population parameters from sample data; - evaluate statistical hypotheses; - apply least square regression analysis.

Contenuti

1. Introduction to data: Data basics; Sampling principles; Experiments and observational studies
2. Summarizing data: Examining numerical data; Considering categorical data
3. Probability: Defining probability; Conditional probability; Bayes theorem
4. Random variables: Discrete and continuous; Expectation;
5. Distributions of random variables: Normal; Geometric; Bernoulli; Binomial
6. Foundations for inference: Point estimates; Confidence intervals; Hypothesis testing
7. Linear Regression

Testi/Bibliografia

David M Diez, Christopher D Barr, Mine C ̧etinkaya-Rundel, OpenIntro Statistics.

You can download a free pdf version here: https://openintro.org/book/os/

Metodi didattici

Lectures.

Modalità di verifica e valutazione dell'apprendimento

Written exam (2 h), with multiple open questions about all topics covered.

The assessments methods of the course Intended Learning Outcomes is the following (all assessed via written open-ended questions):

• ILO 1 Analyze a dataset using numerical indexes and graphical representations;
• ILO 2 Apply basic tools of probability theory;
• ILO 3 Produce estimates of population parameters from sample data;
• ILO 4 Evaluate statistical hypotheses;
• ILO 5 Apply least square regression analysis.

Strumenti a supporto della didattica

Virtuale (virtuale.unibo.it) contains all the material used during the classes.

Link ad altre eventuali informazioni

https://www.unibo.it/sitoweb/monica.chiogna2/

Orario di ricevimento

Consulta il sito web di Simone Tiberi