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Computational statistics

This course deepens your knowledge in statistical programming. The course provides tools useful in design of statistical surveys, estimation, hypothesis testing and Bayesian analysis. The course presents some basic principles for numerical computing, numerical matrix algebra, solutions to equations, function optimization, and simulation techniques

This course gives you knowledge about the basic principles of numerical computing. You will learn how to design and organize algorithms for function optimization, integration and simulation of distributions and how to solve statistical computing problems with help of statistical software. You will also learn how to carry out simulation experiments.

  • Course structure

    The course is given at day time, full time.

    The course forms a part of the Master's Program in Statistics, but it can also be studied as a freestanding course.

    Teaching format

    The teaching forms consists of lectures and computer labs. The course is given in English.

    Course Information

    More information for registered students will be found in Athena.

    Assessment

    Examination will be in the form of a written test and a written hand in assignment.

    Examiner

    Teachers Spring semester 2021

    Course coordinator

    Frank Miller

    You will find Frank's reception hours in the link above. If you wish to visit Frank outside of his reception hours, you are welcome to e-mail her for an appointment.

    Teaching assistants

    Mahmood Ul Hassan

  • Contact

    Teachers Spring semester 2021

    Course coordinator

    Frank Miller

    You will find Frank's reception hours in the link above. If you wish to visit Frank outside of his reception hours, you are welcome to e-mail her for an appointment.

    Teaching assistants

    Mahmood Ul Hassan

    If you have questions about studying at the Department of Statistics, please contact our study- and career counselor: Jenny Rosen.