Basic Mathematical Statistics
Matematisk statistik kallas ibland ”slumpens matematik” och kunskaper inom området är viktigt för en ingenjör. I sannolikhetsläran får du en överblick över de vanligaste matematiska beskrivningarna för slumpmässiga förlopp, medan du i statistisk inferens möter några vanliga statistiska metoder för analys av insamlade data, t.ex. t-test och regressionsanalys.
Vid praktiskt arbete med data är det viktigt att kunna välja en lämplig metod för ett givet problem, och att kunna utvärdera resultatet från en metod och dra rimliga slutsatser. I kursen arbetar du i datorövningar med frågeställningar kring data och tillämpar mot slutet dina kunskaper i ett eget litet projekt, baserat på problemställningar inom energisystem.
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Syllabus
MS0065 Basic Mathematical Statistics, 5.0 Credits
Grundläggande matematisk statistikSyllabus approved
2013-10-23Subjects
Mathematical StatisticsEducation cycle
First cycleModules
Title | Credits | Code |
---|---|---|
Theory | 4.00 | 1002 |
Project | 1.00 | 1003 |
Advanced study in the main field
First cycle, less than 60 credits from first-cycle courses as entry requirements(G1F)Grading scale
Language
SwedishPrior knowledge
The equivalent of 20 credits in mathematics.Objectives
The aim of the course is to give an introduction to probability theory and statistical concepts and to provide applied examples. After the course the student should be able to• apply basic probability concepts and statistical principles
• formulate a given problem in statistical terms
• describe the most common statistical methods including the conditions under which they can be applied.
• choose a suitable statistical method for a given problem
• carry out a statistical analysis from the chosen method
• interpret and evaluate results correctly and draw reasonable conclusions
• use statistical software
• carry out a statistical group project independently
Content
The course is built on lectures, computer exercises and a small statistical project. Exercises are related to the field of energy, among others.The main moments are as follows: Descriptive statistics: Measures of mean and variation, different diagrams. Probability theory: Sample space, probability laws, random variables, probability distributions. Inference: Point estimation, confidence intervals, hypothesis testing, non-parametric methods. Regression and correlation. Practical statistical computing.
Formats and requirements for examination
Passed written and oral exercise. Passed written examination.- If the student fails a test, the examiner may give the student a supplementary assignment, provided this is possible and there is reason to do so.
- If the student has been granted special educational support because of a disability, the examiner has the right to offer the student an adapted test, or provide an alternative assessment.
- If changes are made to this course syllabus, or if the course is closed, SLU shall decide on transitional rules for examination of students admitted under this syllabus but who have not yet passed the course.
- For the examination of a degree project (independent project), the examiner may also allow the student to add supplemental information after the deadline. For more information on this, please refer to the regulations for education at Bachelor's and Master's level.
Other information
- The right to take part in teaching and/or supervision only applies to the course date to which the student has been admitted and registered on.
- If there are special reasons, the student may take part in course components that require compulsory attendance at a later date. For more information on this, please refer to the regulations for education at Bachelor's and Master's level.