Applied Statistical Methods

7.5 credits

Course, Bachelor's level, 2ST094

Expand the information below to show details on how to apply and entry requirements.

Location
Uppsala
Pace of study
100%
Teaching form
On-campus
Instructional time
Daytime
Study period
5 December 2025–18 January 2026
Language of instruction
The course will be taught in English, if needed
Entry requirements

At least 15 credits from Statistics A, 30 credits

Selection

Final school grades (60%) - Swedish Scholastic Aptitude Test (40%)

Fees
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
  • First tuition fee instalment: SEK 11,250
  • Total tuition fee: SEK 11,250

Read more about fees.

Application deadline
15 April 2025
Application code
UU-26628

Admitted or on the waiting list?

Registration period
24 July 2025–31 August 2025
Information on registration from the department

Expand the information below to show details on how to apply and entry requirements.

Location
Uppsala
Pace of study
100%
Teaching form
On-campus
Instructional time
Daytime
Study period
1 May 2026–7 June 2026
Language of instruction
The course will be taught in English, if needed
Entry requirements

At least 15 credits from Statistics A, 30 credits

Selection

Final school grades (60%) - Swedish Scholastic Aptitude Test (40%)

Fees
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
  • First tuition fee instalment: SEK 11,250
  • Total tuition fee: SEK 11,250

Read more about fees.

Application deadline
15 October 2025
Application code
UU-76628

Admitted or on the waiting list?

Registration period
18 December 2025–18 January 2026
Information on registration from the department

About the course

This course in applied statistics focuses on data analysis using statistical methods. The course consists of a number of cases (homework assignments) and for each of these, you hand in a written report and do an oral presentation of the report. Examination of the course is based on the homework assignments; no traditional exam is given.

You will learn to apply appropriate statistical tools to various data sets and research questions. The course requires a solid understanding of basic probability theory and statistical inference, basic econometrics and time series analysis. Examples of methods used are multiple regression, logistic regression and ARIMA models. 

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