All courses

Course content

Linear regression. Multiple linear regression. 2-level factorial design. Analysis of variance. Multivariate normal distribution. Principal component analysis. Contingency tables. Expected value and variance to functions of random variables.

Learning outcome

The course is constructed for students at industrial mathematics, and for others who want a more extensive statistical background than that provided by the first Statistics class. The students learn basic statistical models and methods that are very common in industry and technology.

Learning methods and activities

Classes, practical exercises using appropriate software, and a compulsory project. The final grade is a weighted sum based on both the written final exam (80%) and on a grade in the project (20%). Retake of examination may be given as an oral examination. The lectures will be given in English if they are attended by students from the Master's Programme in Mathematics for International Students.

Compulsory assignments

• Exercises

Recommended previous knowledge

The course is based on TMA4240/4245 Statistics, or equivalent.

Required previous knowledge

Course materials

Will be announced at the start of the course.

Credit reductions

Course code	Reduction	From	To
SIF5038	2.5	2008.01.09
SIF5068	5.0	2008.01.09
ST2202	5.0	2008.01.09
TMA4255	5.0	2008.01.09
TMA4260	5.0	2008.01.09
TMA4270	2.5	2008.01.09