FMSN30 / MASM22, 7,5 credits, A (Second Cycle)

General Information

Elective for: BME4, D4, E4-ae, F4, F4-fm, F4-mai, I4, L4-fe, Pi4-fm, Pi4-biek, Pi4-bam, MMSR1, R4
The course will be given in English
Course code at LTH: FMSN30. Course code at the faculty of science: MASM22.

Contents

Least squares and maximum-likelihood-method; odds ratios; Multiple and linear regression; Matrix formulation; Methods for model validation, residuals, outliers, influential observations, multi co-linearity, change of variables; Choice of regressors, F-test, likelihood-ratio-test; Confidence intervals and prediction. Introduction to: Correlated errors, Poisson regression as well as multinomial and ordinal logistic regression.

Examination details

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Written and oral project presentation, peer assessment and oral exam.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Parts
Code: 0117. Name: Examination.
Credits: 3. Grading scale: TH. Assessment: Oral examination.
Code: 0217. Name: Project 1.
Credits: 1,5. Grading scale: UG. Assessment: Written project report and peer assessment Contents: Linear regression
Code: 0317. Name: Project 2.
Credits: 1,5. Grading scale: UG. Assessment: Written project report and peer assessment Contents: Logistic regression
Code: 0417. Name: Project 3.
Credits: 1. Grading scale: UG. Assessment: Oral project presentation Contents: Other regression models
Code: 0517. Name: Laboratory Work.
Credits: 0,5. Grading scale: UG. Assessment: Computer exercises

Admission

Admission requirements LTH:

FMSF20 Mathematical Statistics, Basic Course or FMSF25 Mathematical Statistics - Complementary Project or FMSF32 Mathematical Statistics or FMSF45 Mathematical Statistics, Basic Course or FMSF50 Mathematical Statistics, Basic Course or FMSF55 Mathematical Statistics, Basic Course or FMSF70 Mathematical Statistics or FMSF75 Mathematical Statistics, Basic Course or FMSF80 Mathematical Statistics, Basic Course

Entry requirements Science faculty:

For admission to the course knowledge equivalent to the courses of at least 60 credits. Among these courses one
of the courses MASA01, Mathematical Statistics: Basic Course, 15 credits,
MASB02 Mathematical statistics for chemists, 7.5 credits, MASB03 Mathematisk statistics for physicists, 9
credits or MASB11 Biostatistics – basic course
, 7.5 credits, should be included. English B or equivalent.

Reading list

Rawlings, J.O., Pantula, S.G., Dickey, D.A.: Applied Regression Analysis - A Research Tool, 2ed. Springer, 1998, ISBN: 0-387-98454-2. Available as e-book.
Alan Agresti: An introduction to categorical data analysis, 2nd ed. Wiley, 2007, ISBN: 978-0-471-22618-5. Available as e-book.

Contact and other information

Director of studies: studierektor@matstat.lu.se
Course homepage: http://www.ctr.maths.lu.se/course/MASM22/
Only one of the courses FMSN30 and FMSN40 may be included in a degree.

The number of participants is not limited.
The course overlaps following course/s: MASM22, FMSN40

Official Course Description

LTH Course Description (SV)
NF Course Description (SV)
LTH Course Description (EN)
NF Course Description (EN)