- Docente: Christian Martin Hennig
- Crediti formativi: 6
- SSD: SECS-S/01
- Lingua di insegnamento: Inglese
- Modalità didattica: Convenzionale - Lezioni in presenza
- Campus: Bologna
- Corso: Laurea in Scienze statistiche (cod. 8873)
Conoscenze e abilità da conseguire
By the end of the course, the student should know the main topics in statistical inference. In particular the student should be able to: 1- derive an estimator and its properties; 2- define and verify parametric and non parametric statistical hypothesis in simple contexts; 3- build confidence intervals; 4 fit a simple linear regression model.
Contenuti
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Random sampling and sampling distributions. Central limit theorem.
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Estimation theory. Point estimation: finite estimator properties. Interval estimation.
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Hypothesis tests: Fisher significance theory
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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.
Testi/Bibliografia
P.S. Mann "Introductiory Statistics" eight edition, Wiley 2013.
J.A. Rice "Mathematical Statistics and Data Analysis" third edition, Duxbury/Thomson/Brooks/Cole 2007.
Lecture notes.
Metodi didattici
Classroom lessons and tutorials
Modalità di verifica e valutazione dell'apprendimento
2 hours written exam. 5/30 marks can be earned from homework activity.
Strumenti a supporto della didattica
Lecture notes.
Orario di ricevimento
Consulta il sito web di Christian Martin Hennig