Measurement MathematicsLaajuus (3 cr)
Code: KMA0128
Credits
3 op
Objective
After passing the course, a studentcan use SPSS for quantative statistical analysis and can analyse statistical reports,has knowledge in numerical methods,knows, how to read algorithms,can apply them in practical problems
Enrollment
19.11.2021 - 09.01.2022
Timing
03.01.2022 - 29.04.2022
Number of ECTS credits allocated
3 op
Mode of delivery
Contact teaching
Unit
Faculty of Technology (LAB)
Campus
Lappeenranta Campus
Teaching languages
- English
Degree programmes
- Bachelor's Degree Programme in Mechanical Engineering and Production Technology (2016-2021)
Teachers
- Päivi Porras
Scheduling groups
- Luennot (Size: 0. Open UAS: 0.)
Groups
-
TLPRMEC20S
Small groups
- Lectures
Learning outcomes
After passing the course, a studentcan use SPSS for quantative statistical analysis and can analyse statistical reports,has knowledge in numerical methods,knows, how to read algorithms,can apply them in practical problems
Implementation and methods of teaching
Contact lectures, weekly assignments
Exam retakes
No exam
Contents
Basics of statistical analysis
- measures of location and deviation
- hypothesis tests,
- correlation,
- regression)
Numerical methods
- interpolation and extrapolation
- curve fitting
- numerical derivation
- numerical integration
- numerical differential equations
Assessment criteria
Grading:
20% learning diary (max 20 points)
40% statistical analysis (max 40 points)
40% numerical methods (max 40 points)
Grade 5: at least 90% of total scores
Grade 4: at least 80% of total scores
Grade 3: at least 70% of total scores
Grade 2: at least 60% of total scores
Grade 1: at least 50% of total scores
Failed: < 50% of max scores
Assessment scale
1-5