Inferensteori

Course Coordinator/Lecturer
Andriy Andreev, tel 08-16 2570, B739 (Building B, floor 7), e-mail: andriy.andreev@stat.su.se

General information

• University credits: 7.5 ETCS points
  
• The course vill be given in English
  
• The course schedule will be updated shortly: lectures will start in late January
• The detailed teaching plan can be found here.

Prerequisites and special admittance requirements
At least 90 ECTS credit points in Statistics or equivalent.

Aim
Statistical models have been successfully applied in many different fields, such as education, psychology, medicine, economics, and so forth. With the variety of statistical methods that are available nowadays, the natural question is about how these methods tie together as a whole? The goal of this course is to give the students a thorough theoretical ground in understanding of the basic fundamentals and principles that underlie statistical inference and applications of statistical methodologies. Lectures will explain the theoretical origins and practical implications of statistical formulae whereas computer exercises will involve applications of statistical modeling and inference to real data, thereby helping students to control their own comprehension of important statistical concepts.

Learning outcomes
After completing the course, students should be able to

• explain how statistical inference arises from the first principles of probability theory
• explain general methods of data reduction such as sufficiency, likelihood and ancillarity
• derive the main principles of finding and evaluating point estimators, interval estimators and test statistics
• explain principles of asymptotic evaluation of point estimators and tests
• understand how data can be interpreted in the context of a statistical model
• integrate knowledge from the different parts of the course when solving problems

Literature
The main course book is

• Casella G. & Berger R. L. Statistical Inference. Second Edition, Duxbury Press (Thomson Learning Academic Resource Center), 2007 (recommended buying).

Examination/Assessment
The course examination consists of two parts, written exam and computer exercises.
The course grade is based on the written exam which can contain material from computer exercise sessions.
Exam from March 2010        Exam from March 2010 solutions

Computer labs
Computer lab 1 -->>
Computer lab 2 -->>

Useful links
Statistical Inference, Duke University, 2007 -->>

Föreläsningsanteckningar (Notes)
Bayesian Methods and Subjectiv Probability - Daniel Thorburn

NB! These notes are from spring 2008 and written in Swedish. They are not official for the current course, but could be useful.