ML2104 Applied Industrial Statistics 7.5 credits
Content and learning outcomes
Course contents
The course consists of three parts. The first part is an introduction to data analysis and descriptive statistics with applications within quality technology. The second part is stochastic simulation, and predictions with application in risk analysis. The third part is multifactorial experimental design by using statistical methods and orthogonal matrices.
An important part of the content is to adapt data to a possible statistical distribution to be used at stochastic simulation.
Intended learning outcomes
The aim is to give the participants possibilities to use advanced statistical methods for data analysis, predictions and risk analysis as decision support within engineering related fields
On completion of the course the participants should be able to
- Analyse and present multidimensional data sets from industrial applications
- Used statistical distributions in stochastic simulation, based on given data
- Make stochastic simulations by using Monte Carlo techniques
- Explain what the simulation results say about risk and possibilities
- Use common methods within qualitative risk analysis, as a complement to numerical methods
- Make a complete risk analysis by using both qualitative and quantitative data
- Use the Design of Experiments method to evaluate multifactorial dependencies in risk analyses and predictions
- Write risk analysis reports which are understandable for all involved parties
Literature and preparations
Specific prerequisites
A basic course in probability theory and statistics comparable with SF1901, Probability and Statistics or ML1018, Basic industrial statistics or the equivalent.
Recommended prerequisites
Equipment
Computer lab with @Risk software (available in Södertälje)
Literature
Föreläsningsanteckningar, kursbok kommer beslutas i juni 2014
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
Examination
- TEN1 - Examination, 3.0 credits, grading scale: A, B, C, D, E, FX, F
- ÖVN1 - Assignments, 4.5 credits, grading scale: P, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
Other requirements for final grade
Approved homework and laboratory exercises
Approved written examination
Opportunity to complete the requirements via supplementary examination
Opportunity to raise an approved grade via renewed examination
Examiner
Ethical approach
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.