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Data Analyses and Interpretation (5 cr)

Code: YA00BR16-3004

General information


Enrollment

01.09.2022 - 31.12.2022

Timing

01.01.2023 - 31.05.2023

Number of ECTS credits allocated

5 op

Virtual portion

5 op

RDI portion

2 op

Mode of delivery

Distance learning

Unit

Business

Teaching languages

  • Finnish

Degree programmes

  • MASTER´S DEGREE IN BUSINESS MANAGEMENT

Teachers

  • Katri Takala
  • Aki Kortelainen

Groups

  • AYM22S
    AYM22S
  • SYT22S
    SYT22S
  • TLY22S
    TLY22S
  • LYL22SV
    LYL22SV
  • LYL22S
    LYL22S
  • ALY22S
    ALY22S
  • SJY22S
    SJY22S

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.