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Data Analyses and Interpretation (5 cr)

Code: YA00BR16-3007

General information


Enrollment
03.01.2026 - 01.02.2026
Registration for introductions has not started yet.
Timing
02.02.2026 - 31.05.2026
The implementation has not yet started.
Number of ECTS credits allocated
5 cr
Local portion
5 cr
Mode of delivery
Contact learning
Unit
KAMK Master School
Teaching languages
Finnish
Degree programmes
Master´s Degree in Responsible Business Management
Teachers
Arja Oikarinen
Aki Kortelainen
Groups
SJY25S
SJY25S
SYT25S
SYT25S
SKY25S
SKY25S
LYL25SV
LYL25SV
LYL25S
LYL25S
ALY25S
ALY25S
AYM25S
AYM25S
Course
YA00BR16
No reservations found for realization YA00BR16-3007!

Objective

Student
- is proficient in qualitative and quantitative data processing and analysis methods and is able to apply them in research and development activities
- can analyse and interpret qualitative and quantitative data
- is able to interpret and use scientific publications in research and development activities at work and in the work community
- master the basics of combining, linking and merging data and interpreting data according to mixed methods
- can critically assess the reliability and ethics of the processing, analysis and interpretation of data and the potential for their use
- master the key research methods related to research and development in their field

Content

Requirements for qualitative research data and conditions for data analysis
Processing, analysis, interpretation and quantification of qualitative research data
Different types of content analysis
Requirements and conditions for the analysis of quantitative research data
Processing, analysis and interpretation of quantitative survey data
Combining qualitative and quantitative data (mixed methods)

Evaluation scale

0 - 5

Assessment criteria, approved/failed

Approved
The student masters the basic concepts related to different types of data and is able to apply them. The student masters the basics of processing, analysis and interpretation of qualitative and quantitative data. The student is able to critically analyse and interpret qualitative and quantitative data. The student is able to perform statistical runs in a planned and correct manner and to analyse and interpret the results of analyses.

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