IX1501 Mathematical Statistics 7.5 credits

Matematisk statistik

Please note

The information on this page is based on a course syllabus that is not yet valid.

  • Education cycle

    First cycle
  • Main field of study

    Mathematics
    Technology
  • Grading scale

    A, B, C, D, E, FX, F

Course offerings

Autumn 19 TIDAB TIEDB for programme students

Autumn 18 for programme students

Intended learning outcomes

General Objectives

After course completion the student should be able to:

  • formulate, analyze and solve problems in statistics significant to in the ICT sphere.
  • apply and develop statistical models with the aid of mathematical programming language.
  • review and comment a given solution to a problem.
  • comment domain and propose improvements to a statistical model.
  • make presentations of solutions of a statistical problem.

Detailed Objectives

After course completion the student should be able to:

  • apply basic stochastic models and use these to determine summary measures and probabilies.
  • use normal approximation according to CLT.
  • apply basic statistical models to an experiment.
  • specify a standard model and comment the fitness for given data.
  • describe data with summary measures, such as mean, variance and covariance.
  • present data graphically in a suitable way.
  • compute point estimates and confidence intervals.
  • estimate error risks in hypothesis testing.
  • compute correlation and regression line.

Course main content

Probability theory: probability, conditional probability, independenceone-dimensional random variablesbriefing about multi-dimensional random variablescommon distributionsmeasures (location, spreading and dependence) Law of Large Numbers, Central Limit Theorem Statistics: point estimates, confidence intervalshypothesis testregression analysis, correlation, graphical presentation of data.

Disposition

The teaching method is problem oriented and computer aided. The education time is evenly distributed among the three main topics

  • conceptual understanding and modelling
  • algorithms
  • conclusions and synthesis

Eligibility

Entrance qualifications:

  • IX1303 - Algebra och Geometry
  • IX1304 - Calculus

Literature

Examination

  • INLA - Assignment, 3.5, grading scale: P, F
  • TENA - Written exam, 4.0, grading scale: A, B, C, D, E, FX, F

The examiner decides, in consultation with KTH's coordinator for disabilities (Funka), about possible adapted examination for students with documented, permanent disabilities. The examiner may permit other examination format for re-examination of individual students.

Requirements for final grade

  • Written exam (TEN1; 3,5 credits)
  • Problem assignments (INL1; 4,0 credits)

Offered by

EECS/Communication

Contact

Ki Won Sung (sungkw@kth.se)

Examiner

Håkan Olsson <hakano@kth.se>

Version

Course syllabus valid from: Autumn 2019.
Examination information valid from: Autumn 2019.