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SF1915 Probability Theory and Statistics 6.0 credits

The overall purpose of the course is that the student should be well acquainted with basic concepts, theory, models and solution methods in probability theory and statistical inference.

Choose semester and course offering

Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.

Application

For course offering

Autumn 2024 CMAST3/CITEH programme students

Application code

50556

Headings with content from the Course syllabus SF1915 (Autumn 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Basic concepts such as probability, conditional probability and independent events. Discrete and continuous random variables, in particular one dimensional random variables. Measures of central tendency, dispersion and dependence of random variables and data sets. Common distributions and models, such as the normal, binomial and Poisson distributions. The Central limit theorem and the Law of large numbers.

Descriptive statistics. Point estimates and general methods of estimation, such as maximum likelihood estimation and the method of least squares. General confidence intervals and in particular confidence intervals for the mean and variance of normally distributed data. Confidence intervals for proportions and for difference in means and proportions. Statistical hypothesis testing. Chi2-tests of goodness of fit, homogeneity and independence. Linear regression.

Intended learning outcomes

To pass the course, the student should be able to

  • solve problems that require knowledge about standard concepts and methods in probability theory
  • solve problems that require knowledge about standard concepts and methods in statistics

Literature and preparations

Specific prerequisites

Completed ourse in SF1625 Calculus in one variable. 

Recommended prerequisites

SF1626 Calculus in Several Variable, SF1624 Algebra and Geometry 

Equipment

No information inserted

Literature

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

Complemental material from the department.

Examination and completion

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

Grading scale

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

Examination

  • TEN1 - Examination, 6.0 credits, grading scale: A, B, C, D, E, FX, 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.

The examiner decides, in consultation with KTHs Coordinator of students with disabilities (Funka), about any customized examination for students with documented, lasting disability. 

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

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

Add-on studies

No information inserted

Contact

Björn-Olof Skytt (bos@kth.se)

Supplementary information

Only for students enrolled in the Degree Programme in Mechanical Engineering (CMAST).