Syllabus 2008/2009 FMS601

Syllabus academic year 2008/2009
(Created 2008-07-17.)

MATHEMATICAL STATISTICS

FMS601

Higher education credits: 4,5. Grading scale: TH. Level: G1 (First level). Language of instruction: The course will be given in Swedish. FMS601 overlap following cours/es: FMS032, FMS033, FMS035, FMS032, FMS033, FMS035 och FMS086. Compulsory for: IBYA2, IBYI2, IBYV2. Course coordinator: Anna Lindgren, director of studies, anna@maths.lth.se, Matematisk statistik. Assessment: Written exam and compulsory computer exercises. Further information: The course may not be included together with FMS032 or FMS035. Home page: http://www.maths.lth.se/matstat/kurser/fms601/.

Aim
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 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.

Knowledge and understanding
For a passing grade the student must

be able to relate questions regarding random variation and observed data to the concepts of random variables, distributions, and relationships between variables,
be able to explain the concepts of independence, probability, distribution, expectation, and variance,
be able to calculate the probability of an event, and the expectation and variance from a given distribution,
be able to describe fundamental techniques for statistical inference and be able to use them on basic statistical models.

Skills and abilities
For a passing grade the student must

be able to construct a simple statistical model describing a problem based on a real life situation or on a collected data material,
be able to choose, perform, and interpret a statistical procedure that answers a given statistical problem,
be able to use statistical terms within the field in writing.

Contents
Descriptive statistics. Axoims of probability, conditional probability, independent events. Stochastic variables, expectation, and variance. Normal distribution, binomial distribution, and other important distributions. Functions of stochastic variables. Point estimates, interval estimates, hypothesis testing. Methods for normally distributed data. Linear regression.

Literature
Vännman, K.: Matematisk statistik. Studentlitteratur, 2 uppl. 2001. ISBN: 91-44-01690-5.