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SF1903 Probability and Statistics 7.5 credits

Information per course offering

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Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus SF1903 (Autumn 2007–)
Headings with content from the Course syllabus SF1903 (Autumn 2007–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Basic concepts like probabilities, conditional probabilities and independent events. Discrete and continuous random variables, especially one dimensional random variables. Measures of location and scale of random variables and data sets. Common distributions and models: normal, binomial and Poisson distribution. Central limit theorem and Law of large numbers.

Descriptive statistics. Graphical visualisation of data sets.

Point estimates and general methods of estimation as the method of maximum likelihood and least squares. General confidence intervals but specifically confidence intervals for mean of normally distributed observations. Confidence intervals for proportions, difference in means and proportions.

Testing statistical hypothesis. Chi2-tests. Linear regression.

Intended learning outcomes

To pass the course, the student should be able to do the following:

  • construct elementary statistical models for experiments
  • state standard models and explain the applicability of the models in given examples
  • calculate expectation and variance of probability distributions
  • summarize data sets with descriptive statistics and present data graphically
  • calculate estimates of unknown quantities with standard methods and quantify the uncertainty in these estimates
  • describe how measuring accuracy affect conclusions and quantify risks and error probabilities when testing statistical hypothesis

To receive the highest grade, the student should in addition be able to do the following:

  • Combine all the concepts and methods mentioned above in order to solve more complex problems.

Literature and preparations

Specific prerequisites

Basic differential and integral calculus.

Literature

Blom et al., Sannolikhetsteori och statistikteori med tillämpningar upplaga 5, Studentlitteratur.

Examination and completion

Grading scale

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

Examination

  • TEN1 - Examination, 4.5 credits, grading scale: A, B, C, D, E, FX, F
  • LAB1 - Laboratory Work, 3.0 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

If the course is discontinued, students may request to be examined during the following two academic years.

Other requirements for final grade

Written examination.
Computer assignments.

Examiner

No information inserted

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Technology

Education cycle

First cycle