- Docente: Christian Martin Hennig
- Credits: 6
- SSD: SECS-S/01
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: First cycle degree programme (L) in Statistical Sciences (cod. 8873)
Learning outcomes
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.
Course contents
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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.
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Analysis of variance.
Readings/Bibliography
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.
Teaching methods
Classroom lessons and tutorials
Assessment methods
2 hours written exam. 5/30 marks can be earned from homework activity.
Teaching tools
Lecture notes.
Office hours
See the website of Christian Martin Hennig