Statistical Data Analysis and Experiment DesignLaajuus (5 cr)
Code: TE00BT90
Credits
5 op
Objective
- Data file formats and file reading.
- Data cleansing, outliers and missing data
- Sampling and descriptive statistics
- Statistical tests, Z-test, F-test and Student’s t-test
- ANOVA
- Regression analysis
- Nonlinear curve fitting
- Measurement ranges
Enrollment
01.06.2024 - 01.09.2024
Timing
04.09.2024 - 15.12.2024
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Campus
Lemminkäisenkatu
Teaching languages
- English
Degree programmes
Teachers
- COS Opettaja
- Matti Teittinen
Groups
-
MKEMIK22
Objective
- Data file formats and file reading.
- Data cleansing, outliers and missing data
- Sampling and descriptive statistics
- Statistical tests, Z-test, F-test and Student’s t-test
- ANOVA
- Regression analysis
- Nonlinear curve fitting
- Measurement ranges
Evaluation scale
H-5
Enrollment
01.06.2023 - 30.09.2023
Timing
01.01.2023 - 15.12.2023
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
Engineering and Business
Teaching languages
- English
Degree programmes
Teachers
- Matti Teittinen
Scheduling groups
- Vain avoimen AMK:n opiskelijoille (Tutkinto-opiskelija ilmoittaudu joka tapauksessa, toteutus ei ole vain avoimen opiskelijoille) (Size: 5. Open UAS: 5.)
Groups
-
MKEMIK21
-
MKEMIS20
Small groups
- For Open UAS students only
Objective
- Data file formats and file reading.
- Data cleansing, outliers and missing data
- Sampling and descriptive statistics
- Statistical tests, Z-test, F-test and Student’s t-test
- ANOVA
- Regression analysis
- Nonlinear curve fitting
- Measurement ranges
Evaluation scale
H-5
Enrollment
01.12.2021 - 24.01.2022
Timing
01.01.2022 - 31.05.2022
Number of ECTS credits allocated
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Teaching languages
- Finnish
- English
Teachers
- Patric Granholm
Teacher in charge
Patric Granholm
Groups
-
MKEMIS19
Objective
- Data file formats and file reading.
- Data cleansing, outliers and missing data
- Sampling and descriptive statistics
- Statistical tests, Z-test, F-test and Student’s t-test
- ANOVA
- Regression analysis
- Nonlinear curve fitting
- Measurement ranges
Materials
To be announced later
Teaching methods
Online studies
Student workload
Self study 120 h
Guided study 15 h
Content scheduling
- Data file formats and file reading.
- Data cleansing, outliers and missing data
- Sampling and descriptive statistics
- Statistical tests, Z-test, F-test and Student’s t-test
- ANOVA
- Regression analysis
- Nonlinear curve fitting
- Measurement ranges
- Accuracy and error estimates
- One factor experiments
- Multifactor experiments
Evaluation scale
H-5
Assessment methods and criteria
Assignments
Assessment criteria, fail (0)
< 50 % of the scores
Assessment criteria, satisfactory (1-2)
50 - 75 % of the scores
Assessment criteria, good (3-4)
75 - 90 % of the scores
Assessment criteria, excellent (5)
> 90 % of the scores