79189 - Statistics II

Course Unit Page

Academic Year 2018/2019

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

  • Random sampling and sampling distributions. Central limit theorem.

  • Estimation theory. Point estimation: finite estimator properties. Interval estimation.

  • Hypothesis tests: Fisher significance theory

  • 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.

  • 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