Skip to main content
Link list

Study Guide

Choose language
system.sr-kielenvaihto_fi system.sr-kielenvaihto_en

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

Open in new tab
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

Open in new tab
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