This page gives description of the course. All other information including detailed weekly plan is presented at the Syllabus page.

Structure of the course

The teaching of the course is organised around the following components: lectures providing an overview of the theory and assisted computer labs. The student work with Matlab or Python programming language on their choice, the main teaching tool is a web-based Virtual Learning Environment (VLE) described below.

Virtual Learning Environment (VLE)

Mathematical Sciences department's Stats VLE is a web-based system providing students with all the necessary tools to learn basic Probability and Statistics and practice problem solving on your own. It contains a variety of computer generated questions covering the course curriculum as well as all necessary supporting materials: statistical tables, manual, demos, etc. One may re-run the question-solution cycle as many times as felt necessary to deepen understanding of Statistics and to practice the techniques. It is complemented by the Study Guide with necessary theory which is directly accessible from within the VLE. Here are detailed instructions on how to get started with the VLE.

Assessment

The course has total 4 LADOK credits. The grade is based on the results of two two tests in Week 17 and 21, and the final examination in Week 22 (preliminary date is Monday 30/05 14:00-16:00). You do not need to register cetrally for the exam - the registration will be within the VLE system that the course uses, the details will follow. The students who performed well in both tests are exempt from the final examination, see below. Both the tests and the exam are held within the VLE: you will have access to the linked Study guide. Further details will be explained in due time.

The marking scheme: if T1 is the mark (in percentage) for Test 1, T2 - the mark for Test 2, E - the exam mark, then the overall mark M is derived as follows: if T1 ≥ 40%, T2 ≥ 40% and T1+T2 ≥ 100%, then the student is exempt from the exam and M=0.5 T1 + 0.5 T2. Otherwise, M=E. The final grade is then FAIL, if M<40%; it is 3, if 40% ≤ M < 60%; the grade is 4, if 60% ≤ M < 80%; and it is 5 if M ≥ 80%. The students who are exempt from the exam may, however, choose to take it in attempt to raise their grade. But they must realise that their grade will then be based entirely on E: the results of the tests are not taken into account and the final grade can actually become 3 if E < 60, even if it was 4 or 5 by tests: T1 + T2 ≥ 120%.

The students who have not passed the exam by the end of the course will be asked to take a re-sit examination in August. The test results are not taken into account.

The resit examination is scheduled for Thursday 25th of August 2022 14:00-16:00 in SB-D509 auditorium. You do not need to register centrally for the resit exam either, booking on the VLE is available from Monday 22/08, and come to the exam lab at least 15 minutes before the start of the exam.

Course Literature

The main source is the Study Guide and the other teaching meterials which are available from within the VLE. Also recommended but not compulsory (there are later editions, but much more expensive):

Douglas C. Montgomery and George C. Runger. Applied Statistics and Probability for Engineers, 6th edition, Wiley, 2014. ISBN10: 1118744128, ISBN-13: 9781118744123
Kerstin Vännman and Adam Jonsson. Matematisk statistik, 3rd edition, Studentlitteratur, 2020. ISBN 978-93-44-13324-9
Engelsk-svensk matematisk ordlista.

Recommended reading for Python:

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Programme

See Course programme page.

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