# Syllabus for Applied Statistics

## Syllabus

• 5 credits
• Course code: 1MS026
• Education cycle: Second cycle
• Main field(s) of study and in-depth level: Mathematics A1N, Technology A1N
• Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
• Established: 2010-05-11
• Established by:
• Revised: 2018-08-30
• Revised by: The Faculty Board of Science and Technology
• Applies from: week 24, 2019
• Entry requirements: 120 credits including Probability and Statistics.
English language proficiency that corresponds to English studies at upper secondary (high school) level in Sweden ("English 6").
• Responsible department: Department of Mathematics

## Learning outcomes

On completion of the course, the student should be able to:

• use the most common statistical tests and understand their assumptions and limitations;
• formulate and choose a suitable methodology for testing in a given situation;
• use the most common estimation methods (e.g. method of moments, or the maximum-likelihood method);
• perform estimation in regression models and evaluate a proposed model;
• evaluate results from statistical software (e.g. R).

## Content

Statistical hypothesis testing (interpretation with confidence intervals, p-values), estimation methodology (ML and LS estimation); non-parametric methods, correlation analysis, multiple regression (estimation, prediction, diagnostics).

## Instruction

Lectures, computer sessions. Guest lecture. Case studies where the course content is applied in problems arising in technology, the natural or social sciences.

## Assessment

Written examination at the end of the course (4 credits) combined with assignments given during the course (1 credit).

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Applies from: week 01, 2019

• Alm, Sven Erick; Britton, Tom Stokastik : Sannolikhetsteori och statistikteori med tillämpningar

Liber, 2008

Find in the library

Mandatory

• Kompendium, Grundläggande regressionsanalys. Eva Enquist.

Matematiska institutionen,

Mandatory