Kaisa_2012_3_photo by Veikko Somerpuro

We focus on large sample statistical inference in more detail and with a bit more general assumptions than in the bachelor's level course of statistical inference ('Tilastollinen päättely II'). The first subject will be basic probability results on convergence in probability and distribution.

We will use the lecture notes by Pentti Saikkonen (see, for example, the spring 2016 course page 'Tilastollinen päättely III').

Prerequisites for the course are bachelor level studies in statistics, especially Tilastollinen päättely I and II, Lineaariset mallit I and Todennäköisyyslaskenta I and II.

Lectures 5.9.2017 - 17.10.2017:
Mondays 12.15 - 14.00 in classroom C321 and Tuesdays 10.15 - 12.00 in classroom B322

Exercise classes 11.9.2017 - 16.10.2017:
Mondays 10.15 - 12.00 in classroom B321

Note: First exercise class will be held on Tuesday 12.9. 10.15 - 12.00 and there will be a lecture on Monday 11.9. 10.15 - 12.00.

Ilmoittaudu

Aikataulu

Tästä osiosta löydät kurssin opetusaikataulun. Tarkista mahdolliset muut aikataulut kuvauksesta.

PäivämääräAikaOpetuspaikka
Ti 5.9.2017
10:15 - 12:00
Ma 11.9.2017
12:15 - 14:00
Ti 12.9.2017
10:15 - 12:00
Ma 18.9.2017
12:15 - 14:00
Ti 19.9.2017
10:15 - 12:00
Ma 25.9.2017
12:15 - 14:00
Ti 26.9.2017
10:15 - 12:00
Ma 2.10.2017
12:15 - 14:00
Ti 3.10.2017
10:15 - 12:00
Ma 9.10.2017
12:15 - 14:00
Ti 10.10.2017
10:15 - 12:00
Ma 16.10.2017
12:15 - 14:00
Ti 17.10.2017
10:15 - 12:00

Muu opetus

11.09. - 16.10.2017 Ma 10.15-12.00
Henri Karttunen
Opetuskieli: englanti

Kuvaus

Optional course.

Master's Programme in Mathematics and Statistics is responsible for the course.

The course belongs to the Statistics and Social statistics module.

The course is available to students from other degree programmes.

Bachelor studies

Large sample statistical inference

Recommended time/stage of studies for completion: 1. or 2. year

Term/teaching period when the course will be offered: varying

Delta method and convergence in probability and distribution. Large sample properties of the logarithmic likelihood function and maximum likelihood estimator. Asymptotic test statistics and confidence bounds.

Saikkonen P., Tilastollisen päättelyn jatkokurssi (Luentomoniste); Ferguson T., A course in large sample theory.

Lectures and exercise classes

Exam and excercises, Course will be graded with grades 1-5

Exam, other methods will be described later