Opetussuunnitelmat

Objective

The student is able to use basic quantitative and qualitative data processing tools for collecting, presenting, and analysing data. The student 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.

IBCRI Skills in Critical and Analytical Understanding

Critically review, analyze and understand the information available from academic and professional business sources in the context of reporting Data Analysis results.

IBCOM Communication Skills

Communicate responsibly and effectively in English through oral, written, and digital formats in the context of reporting academic and professional Data analysis results.

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. THE PROSPECTIVE STUDENTS WILL ONLY NEED TO BE PRESENT IN AN INTRODUCTORY WEBINAR HELD AND RECORDED THROUGH ZOOM. 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

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 learning in the forms of tutorials, individual and group works, reflection and guidance. However, if the COVID-19 situation requires the learning will be supported by on-line tutorials.

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 reporting or thesis-related research purpose.

Exam schedules

The detailed and up-to-date information is available in the course workspace.

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 Faculty.

Completion alternatives

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 learning in the forms of tutorials, individual and group work, reflection and guidance. However, if the COVID-19 situation requires the learning will be supported by on-line tutorials.

Detailed and up-to-date information is available in the course workspace.
No alternative completion methods other than available through the course workspace.

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 learning in the forms of tutorials, individual and group work, reflection and guidance. However, if the COVID-19 situation requires the learning will be supported by on-line tutorials.

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.

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 December.
IN the Spring semester the course ends the latest at the end of May.
More details to be announced during the course.

Further information

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 learning in the forms of tutorials, individual and group work, reflection and guidance. However, if the COVID-19 situation requires the learning will be supported by on-line tutorials.
Detailed and up-to-date information is available in the course workspace.

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

Sufficient (1) -

Critical and Analytical Understanding Skills - You show some ability to analyze and evaluate academic and business information relevant to Data Analysis.

Communications Skills - You are able to transmit to a limited extent your and your team’s ideas and findings in English in relation to Data Analysis

Satisfactory (2) -

Critical and Analytical Understanding - You show basic ability to analyze and evaluate academic and business information relevant for Data Analysis.

Communications Skills - You are able to get your main message through when presenting your or your team’s ideas and findings in English but improvement would be needed.

Assessment criteria, good (3)

Good (3) -

Critical and Analytical Understanding Skills - You show ability to analyze and evaluate academic and business information relevant to Data Analysis.

Communications Skills - You are able to transmit in a clear manner your and your team’s ideas and findings in English in relation to Data Analysis.

Very Good (4) -

Critical and Analytical Understanding - You show very good ability to analyse and evaluate academic and business information relevant for Data Analysis.

Communications Skills - You are able to get your main message through when presenting your or your team’s ideas and findings in a very good manner in English.

Assessment criteria, excellent (5)

Excellent (5) -

Critical and Analytical Understanding - You show excellent ability to analyze and evaluate academic and business information relevant for Data Analysis.

Communications Skills - You are able to get your main message through when presenting your or your team’s tideas and findings in a convincing manner in English.

Qualifications

No prerequisites