Statistical Inference for Technological Applications

Education facts

Code: 1TS325

In this course, you will learn about drawing industry-relevant conclusions from collected data (statistical inference) using two computer-intensive methods that often are easier and more powerful than the ones from Classical Statistics you have seen before. The first is almost theory-free and based on creating resampled datasets from the original one. The second method is based on the Bayes theorem while interpreting distributions as measures of uncertainty. You will also study experimental design as well as how and why drawing conclusions using Machine Learning models differs from drawing conclusions using statistical data models.

Entry requirements

Option 1: 120 credits whereof 60 credits in science/engineering, including 20 credits in mathematics, which should include single variable calculus, linear algebra and probability theory/statistics. Participation in Computer Programming I or Programming. Option 2: 120 credits whereof 60 credits in science/engineering. Participation in 25 credits in mathematics/statistics/scientific computing, of which 15 credits should be completed. The 25 credits should include statistics. Participation in Computer Programming I or Programming. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Statistical Inference for Technological Applications

  Uppsala University

  Uppsala

  Start date: 18 January 2027

  End date: 21 March 2027

  Pace of study: 33 %