Statistics (5 cr)
Code: TU00DZ52-3008
General information
- Enrollment
-
06.05.2024 - 18.08.2024
Registration for the implementation has ended.
- Timing
-
19.08.2024 - 15.12.2024
Implementation has ended.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- Mode of delivery
- On-campus
- Unit
- (2019-2024) School of ICT
- Campus
- Karaportti 2
- Teaching languages
- Finnish
- Degree programmes
- Industrial Management
- Teachers
- Rakel Peltola
- Groups
-
TXQ23KIndustrial Management, Double Degree
-
TXQ23ICTIndustrial Management, ICT Business
-
TXQ23SCMIndustrial Management, Supply Chain Management
- Course
- TU00DZ52
Implementation has 32 reservations. Total duration of reservations is 64 h 0 min.
Time | Topic | Location |
---|---|---|
Tue 20.08.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC592
Digitila
|
Thu 22.08.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC592
Digitila
|
Tue 27.08.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC592
Digitila
|
Thu 29.08.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC592
Digitila
|
Tue 03.09.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KME762
Oppimistila
|
Thu 05.09.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC565
Digitila
|
Tue 10.09.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD750
Oppimistila
|
Thu 12.09.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC565
Digitila
|
Tue 17.09.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD569
Oppimistila
|
Thu 19.09.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC565
Digitila
|
Tue 24.09.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC565
Digitila
|
Thu 26.09.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD759
Oppimistila
|
Tue 01.10.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 03.10.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC565
Digitila
|
Wed 09.10.2024 time 10:00 - 12:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC592
Digitila
|
Wed 09.10.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC592
Digitila
|
Thu 24.10.2024 time 10:00 - 12:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD757
Oppimistila
|
Thu 24.10.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD758
Oppimistila
|
Thu 31.10.2024 time 10:00 - 12:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 31.10.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 07.11.2024 time 10:00 - 12:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 07.11.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 14.11.2024 time 10:00 - 12:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 14.11.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 21.11.2024 time 10:00 - 12:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 21.11.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 28.11.2024 time 10:00 - 12:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 28.11.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 05.12.2024 time 12:00 - 14:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMD557
Digitila
|
Thu 05.12.2024 time 12:00 - 14:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
|
Mon 09.12.2024 time 13:00 - 15:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC592
Digitila
|
Mon 09.12.2024 time 16:00 - 18:00 (2 h 0 min) |
Tilastomatematiikka TU00DZ52-3008 |
KMC592
Digitila
|
Objective
The student understands how statistical methods and analysis can be used in decision making.
Content
Probability Calculations
Statistical Methods
Evaluation scale
0-5
Assessment criteria, satisfactory (1)
The student has achieved the course objectives fairly. Students will be able to identify, define and use the concepts and models in the subject area. The student understands the criteria and principles of the expertise development
Assessment criteria, good (3)
The student has achieved the course objectives well, even though the knowledge and skills need improvement in some areas. The student is able to define the course concepts and models and is able to justify the analysis. The student is able to apply the knowledge in study and work situations in the own field. The student understands the importance of expertise in the field of business and is able to analyze his/her own expertise.
Assessment criteria, excellent (5)
The student has achieved the objectives of the course with excellent marks. The student masters commendably the concepts and models in the course. The student is able to make justified and fluent analysis and to present concrete development measures. The students are well prepared to apply their knowledge in study and work situations. Students are able to analyze the business sector expertise and the evolvement of their own expertise.
Assessment criteria, approved/failed
The student has achieved the course objectives fairly. Students will be able to identify, define and use the concepts and models in the subject area. The student understands the criteria and principles of the expertise development.