KsTU-DATALINK
Kumasi Technical University, Ghana
LISA 2020 Network Full Member: 2021

Vision/Mission:

• To be a centre of excellence in producing high calibre graduates in Statistical and Data Sciences suitable to support and sustain the needs of industries, researchers and policy makers for economic development of the country and beyond.

• To create a favourable environment for teaching, research, skills development and entrepreneurship training in Engineering, Science, Technology, Applied Social Sciences for industrial and societal development in Ghana, Africa and beyond.

The Lab is domiciled in the Statistical Sciences Department of the University and decisions relating to the lab will be taken collectively team members of the lab under the chairmanship of the Coordinator/Director.

• • Organize statistical software (such as R Console and SPSS) training for students and staff who lack this capacity by way of workshop.

  • Introduce some members of staff to advance analytical tools in Python, SQL and so on to build their capacity in handling big data. This will also as a refresher course to assist in handling some programming courses in Bachelor of Technology in Data Science programme.

  • Form Statistical Sciences Clubs/Associations across the Senior High Schools within our university catchment area, at least for starters, and organize motivational talks to underscore the need for pursuing degrees in Statistical and Data Science disciplines. This will help whip up their appetites, with particular target at females, to increase enrollment in Statistical and Data Science disciplines as current enrollments figures leave room for improvement.

  • Groom young researchers, particularly in the area of Statistical and Data Sciences, through periodic capacity building workshops. This will cover few of our students, at the beginning, till such a time that the lab can expand on the numbers. Female students would be given priority in this endeavor.

  • Provide a platform for statistical experiments necessary for developing a better understanding of the theoretical aspect of the subject under study. This service will be primarily to students and other staff, from the likes of social sciences, humanities, engineering, etc who require same.

  • It will help store data obtained from various sources such as industry, local government and research establishments suitable for statistical analysis in systematic order.

  • Provide good statistical examples in different topics in statistics and their solutions when needed.

  • Will also serve as an avenue to offer prereview of academic papers regarding methods and results to faculty staff before submission to journals.

  • Provide a platform for statistical experiments necessary for developing a better understanding of

  • Serve as publishing of an annual statistical bulletin from medium-to-long term.

  • Impact government socio-economic agenda based on research.

  • Impact industry based on collaborative research drive.

KsTU-DATALINK expects the following outcomes based of its activities:

RESEARCHERS

• improved research and scientific writing skills

• Improved quality and quantity of publications

Metrics: Organize routine workshops for our students on writing quality academic papers using experienced Senior Lecturers and Professors as resource persons. Also, there will be forum for knowledge sharing on how spot the right journal for publications. Luckily, some of us have participated in ISI world congresses from 2015 to date and have had the benefits of participating in various sections on how to pick the right journal for a paper.

GENDER BALANCED ENROLLMENT

• Increase the number of female enrollments

• Increase student participation in KsTU-DATALINK

Metrics: Form Statistical Sciences Clubs/Associations across the Senior High Schools within our university catchment area, for starter. Also, organize motivational talks to underscore the need for pursuing degrees in Statistical and Data Science disciplines. Again, organize outreach events for to increase general enrollment in Statistical and Data Science disciplines.

LEADERS

• Policy developed from evidence.