Data Analysis in Business Management (5cr)

Evaluation scale

0-5

Content scheduling

The detailed and up-to-date information are available in the course workspace.
Weekly lectures, workshops, and assignments.
In the Fall semester the course ends the latest in the third week of De-cember.
In the Spring semester the course ends the latest at the end of May.
More details to be announced during the course.

Objective

You are able to use basic quantitative and qualitative data processing tools for collecting, presenting, and analysing data. You understands the basic concepts in quantitative and qualitative data analysis. The course will focus on practical examples including the use of SPSS and NVivo tools.

ILO 1
Proactive Development
Develop solutions to current and future business challenges using knowledge, critical reasoning, and analytical skills.

ILO 3
Ethics
Benchmark and demonstrate ethical and responsible managerial behavior in business decision-making.

Execution methods

Hybrid implementation including - classroom teaching and distance learning

Content

Quantitative Part - Data collection, survey method, organizing data, data presentation, descriptive statistics, exploratory data analysis, discrete probability distributions, normal distribution, confidence interval estimation, hypothesis testing, simple linear regression, multiple regression, variance analysis.

Qualitative Part - Basic qualitative research skills for novice including - ethics, traditional interviewing techniques, focus groups, ethnography, action research, unobtrusive measures, historiography, case study, how to manage collected qualitative data and disseminate findings.

Location and time

PLEASE NOTE THAT THIS COURSE IS EXCLUSIVELY SUITED TO ONLINE DELIVERY. ALL TEACHING WILL BE CONDUCTED ONLINE. PLEASE, WAIT FOR THE INSTRUCTOR TO CONTACT YOU WITH ADDITIONAL INFORMATION

Materials

Textbooks:
Quantitative Part:
Data Analysis with SPSS: A First Course in Applied Statistics (4th Edition) Stephen A. Sweet, Karen Grace-Martin, 2012
Qualitative Part:
The Coding Manual for Qualitative Researchers (any edition will do)
Johnny Saldana - Arizona State University, USA

Recommended literature for those who would like to read wider:
Quantitative Part:
Berenson, Levine, and Krehbiel (2004). Basic Business Statistics: Concepts and Applications, 9th Edition.

Qualitative and Mixed Methods Part:
Cresswell (2003). Research Design, Qualitative, Quantitative and Mixed Methods Approaches
Qualitative Research Methods for the Social Sciences, 8/E, Bruce L. Berg, California State University, Long Beach, Howard Lune, Hunter College, 2012

Teaching methods

Lectures, coursework, workshops, virtual studies, individual assignments, group assignments.

Employer connections

Data Analysis skills might be useful íf the student will decide to analyze the data collected (primary data) or obtained (secondary data) during the internship or through working life connection for either internal report-ing or thesis-related research purpose.

Exam schedules

The detailed and up-to-date information is available in the course work-space.
The exam is held online.
There is 1 retake possibility. Specific time and date are announced after the grading of the first attempt and are available in the course work-space.

International connections

The course is available for Double Degree students and Study Abroad students from JAMK's partner institutions around the world. The course includes a significant contribution from JAMK Adjunct International Fac-ulty

Completion alternatives

In general, as Data Analysis in Business Management course forms an integral part of the JAMK IB thesis track system and belongs to the critical path of the thesis process, there is no alternative way to complete the module other than through this implementation. Recognition of prior learning can be granted only in exceptional circumstances, and it is at the lecturer's discretion to approve such arrangements. In practice, no recog-nition of prior learning has been issued to date by the lecturer in charge of this course.
More precise info about recognition of prior learning can be found at: JAMK Degree Regulations, section 17.

Student workload

The primary mode of delivery is a combination of in-class activities on campus and on-line lectures. The lectures will be recorded to support opportunities for 24/7 learning. The in-class activities deepen the learn-ing in the forms of tutorials, individual and group work, reflection and guidance.

Detailed and up-to-date information is available in the course workspace.
Lectures 60 h, virtual study 30 h, assignments 40 h, independent study 25 h

Assessment criteria, satisfactory (1)

Course assessment is based on written reports, presentations, and projects

How learning will be assessed:
The general criteria of the competences of the Bachelor's Degrees awarded by Finnish Universities of Applied Sciences.
The learning outcomes of individual courses are assessed in relation to the objectives of the course concerned. Assessment is based on knowledge, skills and competence in accordance with the National and European Qualifications Framework, level 6.

You will get a grade of ‘one' or 'two' if you are able to demonstrate a basic level of evidence in the following competences:
Learning to learn
Responsible international business management
Ethics

Assessment criteria, good (3)

Course assessment is based on written reports, presentations, and projects

You will get a grade of ‘three' of 'four' if you are able to demonstrate a good level of evidence in the following competences:
Learning to learn
Responsible international business management
Ethics

Assessment criteria, excellent (5)

Course assessment is based on written reports, presentations, and projects

You will get a grade of ‘five’ if you are able to demonstrate an excellent level of evidence in the following competences:
Learning to learn
Responsible international business management
Ethics

Qualifications

No prerequisites

Further information

Detailed and up-to-date information is available in the course workspace.
The assessment method for this course is designed with specific criteria crafted for each assignment/project and the overarching learning objec-tives. Peer evaluation is integrated into the learning process through in-teractive workshops. Detail and specific information regarding assess-ment can be accessed within the dedicated course workspace.