Linear and Logistic Regression

Linear and Logistic Regression / Linjär och logistisk regression

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:

 

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 Links to an external site.

Official Course Description