Visa svensk kursplan
Statistical Methods, 6 ECTS Credits
COURSE CATEGORY   Master´s Programme in Statistics and Data Mining
SUBJECT AREA   Statistics – ST1
  COURSE CODE   732A49
The course provides a theoretical basis of statistical concepts and methods that are required for qualified work and research in statistics.

After completion of the course, the student should be able to:
- use knowledge of the common statistical distributions for building statistical models.
- demonstrate a good understanding of the main principles within point estimation, interval estimation and hypothesis testing,
- demonstrate a good understanding of the main concepts of Bayesian analysis,
- build linear regression models, check their uncertainty and perform model comparison,
- apply methods for sampling from large finite populations,
- apply the basic imputation methods for model building and estimation.
- Concept of probability
- Random variable, common statistical distributions and their properties
- Point- and interval estimation
- Hypothesis testing
- Simple and multiple linear regression, t-test and F-test. Residual and outlier analyses
- Likelihood, prior and posterior distribution, and Bayes theorem
- Concept of Markov chains
- sampling with and without replacement.
- imputation for model building
The teaching comprises lectures, seminars, and computer exercises complemented by self-studies. The lectures are devoted to presentations of concepts, theories and methods. The computer exercises provide practical experience of statistical analysis. The seminars comprise presentations and discussions of various assignments.
Written reports on the computer assignments. 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.

For acceptance to the course, the student must have a bachelor’s degree with a total of at least 90 ECTS credits (1.5 years of full-time studies) in mathematics, applied mathematics, statistics, or computer science. The undergraduate courses in mathematics should include both calculus and linear algebra. Basic undergraduate courses in statistics and computer science are also required.
Documented knowledge of English equivalent to Engelska B/Engelska 6: internationally recognized test, e.g. TOEFL (minimum scores: Paper based 575 + TWE-score 4.5, and internet based 90+TWE-score 20), IELTS, academic (minimum score Overall band 6.5 and no band under 5.5), or equivalent.
The course is graded according to the ECTS grading scale A-F
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.
The course literature is decided upon by the department in question.
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.
Statistical Methods
Statistical Methods
Department responsible
for the course or equivalent:
IDA - Department of Computer and Information Science
Registrar No: LiU-2012-01412   Course Code: 732A49      
    Exam codes: see Local Computer System      
Subject/Subject Area : Statistic - STA          
Level   Education level     Subject Area Code   Field of Education  
A1X   Advanced level     ST1   SA  
The syllabus was approved by the Board of Faculty of Arts and Science 2014-05-28