- Docente: Silvia Cagnone
- Language: English
- Moduli: Paola Bortot (Modulo 1) Silvia Cagnone (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Economics (cod. 8408)
Learning outcomes
The aim of the course is to refresh the pre-requisite knowledge for the STATISTICS course, usually acquired by the student in his/her first cycle degree. At the end of the course the student has a working knowledge of: -probability, conditional probability, probability distributions, sampling distributions, estimation methods (moments, likelihood) and large sample theory.
Course contents
Module 1:
Review of the axiomatic approach to probability
Total Probability Law and Bayes Theorem
Discrete and continuous random variables and properties of some common families of probability distributions (the Binomial, Poisson, Gaussian and Gamma distributions)
Module 2:
Random sampling and sampling distributions.
Estimation theory. Point estimation: finite estimator properties. Interval estimation.
Hypothesis tests: Statistical tests about the mean, a proportion, the variance of a population. Approximate test on a probability. Test on the difference between two means. Test on the difference between two proportions. Test on the difference between two variances. The concept of p-value. Chi square test.
Readings/Bibliography
Mann P.S. "Introductiory Statistics" eight edition, Wiley, 2013.
Borra S., Di Ciaccio A. "Statistica. Metodologia per le scienze economiche e sociali"
Teaching methods
Classroom lessons
Teaching tools
Teacher's notes available at the web-site http://www2.stat.unibo.it/cagnone.
Office hours
See the website of Silvia Cagnone
See the website of Paola Bortot