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SF1910 Applied Statistics 7.5 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.

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Headings with content from the Course syllabus SF1910 (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, both visual and numerical presentation.

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
  • carry out project work in a group with larger and realistic data sets and use statistical methods to support decisions that can support sustainable development

Course disposition

The course consists of lectures, exercises, lab work and a project.

Literature and preparations

Specific prerequisites

Completed course in SF1625 Calculus in one variable. 

Recommended prerequisites

SF1626 Calculus in Several Variable, SF1624 Algebra and Geometry 


No information inserted


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


  • PRO1 - Project, 1.5 credits, grading scale: P, F
  • 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

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Opportunity to raise an approved grade via renewed examination

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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 web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web SF1910

Offered by

Main field of study


Education cycle

First cycle

Add-on studies

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Björn-Olof Skytt (