00914 - Statistics

Learning outcomes

The course provides an introduction to the main methods and basic tools for quantitative analysis of collective phenomena, with the double aim to develop the ability of interpretation and critical evaluation of statistical information and to make students able to produce and autonomously analyze statistical data.

At the end of the course students:

know the basic elements of descriptive and inferential statistics;

are able to read and to understand articles on magazines and/or specialized journals containing results of quantitative analyses;

are able to criticize syntheses and statistical elaborations from total or sampling surveys;

have the necessary skills to autonomously apply some of the tools proper of the statistical methodology for the description and the quantitative analysis of economic and social phenomena.

Course contents

MODULO 1

Statistical variables. Population and sample. Collecting and organizing data. Data set and frequency distributions. Graphic representations. Mean values, mode, median and quantiles. Eterogeneity, variability and inequality measures. Shape: asimmetry and curtosis. Bivariate statistical analysis. Relationships between variables: statistical dependence, covariance and linear correlation. Simple linear regression.

 

MODULO 2

Introduction to sampling and statistical inference. Bayesian theorem. Random variables and probability distributions. Sampling. Point and interval estimation. Hypothesis testing. Linear regression models.

Readings/Bibliography

Student could chose a book in statistics. Some example are:

Borra S., Di Ciaccio A. (2020). Statistica, metodologie per le scienze economiche e sociali, McGraw-Hill.

Levine D.M., Szabat K., Stephan D.F. (2018). Statistica, Pearson.

Pacini B., Raggi M. (2009). Statistica per l'analisi operativa dei dati, Carocci Editore.

Piccolo D. (2010.) Statistica, Il Mulino.

Sullivan M., Zavarrone E. (2015). Fondamenti di statistica, Pearson.

Additional teaching material available at  e-learning Platform: https://iol.unibo.it.

Assessment methods

Links to further information

http://www.unibo.it/docenti/meri.raggi

Office hours

See the website of Meri Raggi

See the website of Annalisa Stacchini