Syllabus academic year 2011/2012
(Created 2011-09-01.)
Credits: 7,5. Grading scale: TH. Cycle: G2 (First Cycle). Main field: Technology. Language of instruction: The course will be given in Swedish. FMS086 overlaps following cours/es: FMS012, FMS032, FMS033, FMS035, FMS085, FMS140, FMS601, FMSF01, KKK065, MAS217 and MASB02. Compulsory for: B3, K3, N3. Course coordinator: Anna Lindgren, Director of studies,, Mathematical Statistics. Prerequisites: At least 6 university credits within the courses FMA410, and FMA430 or FMA435 or FMA025. Recommended prerequisits: Calculus in one variable. Assessment: Written exam, computer exercises, and project report. The course grade is based on the exam grade. Parts: 3. Further information: The laboratory work consists of computer exercises. The course is also given for chemists at the faculty of science with the code MASB02. Home page:

The course is intended to give the student the basics in mathematical modelling of random variation and an understanding of the principles behind statistical analysis. It shall also give the students a toolbox containing the most commonly used models and methods, as well as the ability to use these in practical situations. The emphasis lies on models and methods for analysis of experimental data and measurement errors.

The course fills two purposes, providing a fundamental knowledge of mathematical statistics, as well as giving a foundation for further studies.

The fundamental knowledge is essential to those who, in their professional lives, will not necessarily be involved in statistical analyses on a daily basis, but who, on occasion, will be expected to perform basic statistical tests and present the results to their colleagues. They will also be expected to be able to read and assess the analyses of others.

The course shall also give a basis for further studies, particularly in design of experiments and methods for multidimensional data (Chemometrics).

Knowledge and understanding
For a passing grade the student must

Skills and abilities
For a passing grade the student must

Judgement and approach
For a passing grade the student must

The basis in probability theory and inference, confidence intervals, statistical methods such as design of experiments and regression analysis. Applications: measurement value analysis, different types of errors and their propagation; comparisons of means and variations; concepts and methods for quality control, estimations of proportions; regression analysis, calibration; factorial designs, optimization of experimental parameters, response surfaces. Applications in chemical and biotechnical engineering are of particular interest.

Olbjer, L: Experimentell och industriell statistik. Lund 2000.


Code: 0108. Name: Examination.
Higher education credits: 6. Grading scale: TH. Assessment: Written exam. Contents: See course contents.

Code: 0208. Name: Laboratory Work.
Higher education credits: 0,5. Grading scale: UG. Assessment: Computer exercises.

Code: 0308. Name: Project Work.
Higher education credits: 1. Grading scale: UG. Assessment: Written report. Contents: Application of statistical methods on a relevant problem.