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SYLLABUS

Linear statistical models, 12 ECTS Credits

COURSE CATEGORY   Course within Master´s Programme in Statistics, Data Analysis and Knowledge Discovery MAIN FIELD OF STUDY   Statistik - STA SUBJECT AREA     COURSE CODE   732A22

AIM OF THE COURSE

The course provides basic skills for professional work in which data are explored, modified, modelled and assessed to detect, estimate and verify linear statistical relationships. Having completed the course, the student should be able to: - employ linear statistical models to examine relationships between random variables and derive linear predictors and classifiers from given data sets, - demonstrate insightful assessment of the quality of given data sets and the generalization capacity of identified statistical relationships, - use knowledge about widely used methods for the analysis of linear statistical relationships, - display a good understanding of major principles for the selection, estimation and validation of linear statistical models.

CONTENTS

The course content comprises practical as well as theoretical elements, for example: - computer exercises, - simple and multiple linear regression, logistic regression, Poisson regression, - analysis of variance, and covariance analysis, - point and interval estimation and significance testing of model parameters, - multicolinearity, - residual analysis, - model selection based on hypothesis testing, information criteria, and cross-validation.

TEACHING

Computer exercises in which the students have access to supervision provide practical experience of data analysis. The teaching comprises lectures, seminars, and computer exercises. The lectures are devoted to presentations of theories, concepts, and methods. The seminars comprise student presentations and discussions of assignments. Language of instruction: English.

EXAMINATION

Assignments encompassing computer-based data analysis. One final written examination. Students failing an exam covering either the entire course or part of the course two times are entitled to have a new examiner appointed for the reexamination. Students who have passed an examination may not retake it in order to improve their grades.

ADMISSION REQUIREMENTS

Student’s entering the course should have passed at least one course in basic statistics. Also, courses in calculus and linear algebra are required. Documented knowledge of English equivalent to "Engelska B"; i.e. English as native language or an internationally recognized test, e.g. TOEFL (minimum scores: Paperbased 550 + TWE-score 4.0, computorbased 213 and internetbased 79), IELTS, academic (minimum score: Overall band 6.0 and no band under 5.0), or equivalent.

GRADING

The course is graded according to the ECTS grading scale A-F

CERTIFICATE

Course certificate is issued by the Faculty Board on request. The Department provides a special form which should be submitted to the Student Affairs Division.

COURSE LITERATURE

The course literature is decided upon by the department in question.

OTHER INFORMATION

Planning and implementation of a course must take its starting point in the wording of the syllabus. The course evaluation included in each course must therefore take up the question how well the course agrees with the syllabus. The course is carried out in such a way that both men´s and women´s experience and knowledge is made visible and developed.

Linear statistical models Linear statistical models   Department responsible for the course or equivalent: MAI - Department of Mathematics             Registrar No: 1330/06-41   Course Code: 732A22           Exam codes: see Local Computer System       Subject/Subject Area : Statistik - STA                       Level   Education level     Subject Area Code   Field of Education   A1X   Advanced level     STA   SA   The syllabus was approved by the Board of Faculty of Arts and Science 2006-12-18