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Statistical methods for the Biosciences I - SmB I (generic course) - LPhD014
Provider: Faculty of Science

Activity no.: 5542-20-07-21There are 21 available seats 
Enrollment deadline: 11/11/2020
PlaceDepartment of Mathematical Sciences
Universitetsparken 5, 2100 København Ø
Date and time16.11.2020, at: 09:00 - 31.12.2020, at: 16:00
Regular seats60
Activity Prices:
  - Deltager/Participant from SCIENCE0.00 kr.
  - Deltager/Participant Others5,400.00 kr.
ECTS credits4.50
Contact personNina Weisse    E-mail address: weisse@math.ku.dk
Enrolment Handling/Course OrganiserAnders Tolver    E-mail address: tolver@math.ku.dk
Written languageEnglish
Teaching languageEnglish
Semester/BlockBlock 2
Block noteThe course is taught on the first 6 Wednesdays in block 2.
Scheme groupC
Scheme group noteTeaching is only done on Wednesdays
Exam requirementsThe course is graded as passed/failed. To pass the student must participate in 3 of the 5 course days.
Exam formLøbende bedømmelse
Grading scalePassed / Not passed
Censorship formOne internal examiner.
Course workload
Course workload categoryHours
Theory exercises20.00
Lectures20.00
Preparation60.00

Sum100.00


Content

The course covers basic techniques in model based frequentist statistics exemplified by real applications from the biosciences. Topics covered are: Descriptive statistics, data types, comparison of two samples by parametric and non-parametric methods, analysis of tables of counts, regression analysis of categorical data, linear and multilinear regression, analysis of variance, basic design of experiments, and usage of random effects. The student is also introduced to practical techniques for analyzing data in the open source software package R using the RStudio interface. Recommended prerequisites for the course is some basic statistics course during the participants bachelor or master studies.


Learning outcome

The students are introduces to statistical models commonly used in the biosciences for univariate end-points. The statistical methodology is discussed with emphasis on how models are applied, and the students are trained to do the statistical analyses using the software package R.

After course completion the students are expected to be able to:

Knowledge:
- Describe the elements of frequentist statistics including estimation, confidence intervals, hypothesis tests, model validation.
- Describe the discussed data types.
- Describe the assumptions behind the discussed statistical models.

Skills:
- Identify the data type in a particular dataset, and formulate an adequate statistical model.
- Use R via the RStudio interface to perform the statistical analysis.

Competences:
- Formulate scientific questions in terms of statistical hypothesis.
- Conduct statistical analysis using the discussed models.
- Interpret the results of a statistical analysis.
- Critically reflect over the results, conclusions and limitations of a statistical analysis.
- Judge when to seek help from a skilled statistician.


Literature

R and RStudio is free and open source, and may be downloaded from the internet. As course book we will use

Martinussen, Skovgaard, Sørensen, "A first guide to statistical computations in R", Biofolia 2012, ISBN 978-87-913-1956-3.


Teaching and learning methods
Lectures and exercises including use of computers. In the first half of the course days focus will be on lectures, and in the second half on individual coursework with exercises. But we will switch between these two modes of teaching during the entire day. Participants must bring their own laptops with R and RStudio installed.

Remarks
Course homepage: http://www.math.ku.dk/~pdq668/SmB/SmB_I.html

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