The Department of Statistics, Haramaya University, in collaboration with the Postgraduate Program Directorate and the College of Agriculture and Environmental Sciences, successfully organized a workshop on Professional Competency in Digital Data Collection and Survey Design using KoBoToolbox and Google Forms and Professional Competency in Statistical Data Analysis and Visualization with R from June 16–23, 2026.
The Department of Statistics assigned Mr. Gemechu Asfaw and me as trainers for this important capacity-building initiative. We were honored to deliver both theoretical and hands-on training sessions covering modern approaches to digital data collection, survey design, data management, statistical analysis, and data visualization. The workshop equipped participants with practical skills and real-world applications essential for conducting high-quality research and promoting evidence-based decision-making.
Participants demonstrated remarkable enthusiasm, commitment, and engagement throughout the training. Their active participation, positive feedback, and appreciation of the trainers' dedication, professionalism, and expertise were highly encouraging and reflected the overall success of the program.
We extend our sincere gratitude to the Postgraduate Program Directorate, the College of Agriculture and Environmental Sciences, and the Department of Statistics for their invaluable support and coordination in making this workshop a success. We also express our heartfelt appreciation to all trainees for their active involvement, commitment to learning, and contributions to the interactive training environment.
We warmly invite researchers, postgraduate students, academic staff, development practitioners, NGOs, government organizations, and research institutions to collaborate with the Department of Statistics, Haramaya University, in future professional training and capacity-building initiatives. The Department remains committed to advancing excellence in statistics, data science, research methodology, digital data collection, and statistical analysis to support impactful research, innovation, and informed decision-making.
The Department of Statistics assigned Mr. Gemechu Asfaw and me as trainers for this important capacity-building initiative. We were honored to deliver both theoretical and hands-on training sessions covering modern approaches to digital data collection, survey design, data management, statistical analysis, and data visualization. The workshop equipped participants with practical skills and real-world applications essential for conducting high-quality research and promoting evidence-based decision-making.
Participants demonstrated remarkable enthusiasm, commitment, and engagement throughout the training. Their active participation, positive feedback, and appreciation of the trainers' dedication, professionalism, and expertise were highly encouraging and reflected the overall success of the program.
We extend our sincere gratitude to the Postgraduate Program Directorate, the College of Agriculture and Environmental Sciences, and the Department of Statistics for their invaluable support and coordination in making this workshop a success. We also express our heartfelt appreciation to all trainees for their active involvement, commitment to learning, and contributions to the interactive training environment.
We warmly invite researchers, postgraduate students, academic staff, development practitioners, NGOs, government organizations, and research institutions to collaborate with the Department of Statistics, Haramaya University, in future professional training and capacity-building initiatives. The Department remains committed to advancing excellence in statistics, data science, research methodology, digital data collection, and statistical analysis to support impactful research, innovation, and informed decision-making.
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Together, we measure, discover, and shape a better future through statistics or data science
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Stat 4 ∀ Training Center
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Congratulations Prof✅✅✅
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##Multilevel Modeling for Cross-Sectional Data##
Multilevel modeling can be applied to cross-sectional data when observations are nested within hierarchical groups. For example, individuals may be nested within households, communities, districts, or regions. Although the data are collected at one point in time, multilevel modeling accounts for similarities among individuals within the same group and allows both individual- and group-level factors to be analyzed simultaneously.
For further learning, watch the Stat 4 ∀ Training Center video:
vt.tiktok.com
#MultilevelModeling #CrossSectionalData #DataScience #Statistics #StatisticalModeling
Multilevel modeling can be applied to cross-sectional data when observations are nested within hierarchical groups. For example, individuals may be nested within households, communities, districts, or regions. Although the data are collected at one point in time, multilevel modeling accounts for similarities among individuals within the same group and allows both individual- and group-level factors to be analyzed simultaneously.
For further learning, watch the Stat 4 ∀ Training Center video:
vt.tiktok.com
#MultilevelModeling #CrossSectionalData #DataScience #Statistics #StatisticalModeling
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💻 Summer Data Analytics Bootcamp!
Ready to level up your data skills?
📅 Starting this weekend — Saturday & Sunday
⏰ 8:00 PM – 10:00 PM
Don’t miss out learn, practice, and grow with Python & Data Analytics!
#DataAnalytics #Python #SummerBootcamp #DataScience #LearnPython #20PercentOff
Ready to level up your data skills?
📅 Starting this weekend — Saturday & Sunday
⏰ 8:00 PM – 10:00 PM
Don’t miss out learn, practice, and grow with Python & Data Analytics!
#DataAnalytics #Python #SummerBootcamp #DataScience #LearnPython #20PercentOff
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Kindu Kebede Gebre
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Congratulations Proff💐💐💐
Dear Trainees,
Stat 4 ∀ Training Center has scheduled today’s training session on “Python Application for Machine Learning Models” at 8:00 PM.
Please be punctual and make sure you have completed all the required training requirements before the session begins.
Date: Saturday, August 15, 2026
Time: 8:00 PM
Thank you, and see you at the training session!
Stat 4 ∀ Training Center has scheduled today’s training session on “Python Application for Machine Learning Models” at 8:00 PM.
Please be punctual and make sure you have completed all the required training requirements before the session begins.
Date: Saturday, August 15, 2026
Time: 8:00 PM
Thank you, and see you at the training session!
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Dear Members,
Please find below an opportunity for the NTUST Scholarship 2027 in Taiwan for international students pursuing Master’s and PhD programs. The scholarship offers tuition support and a monthly stipend. The reported application deadline is 11 September 2026.
Please review the eligibility requirements, available programs, required documents, and application procedure carefully before applying. https://scholarshipforphd.com/ntust-scholarship/
Please find below an opportunity for the NTUST Scholarship 2027 in Taiwan for international students pursuing Master’s and PhD programs. The scholarship offers tuition support and a monthly stipend. The reported application deadline is 11 September 2026.
Please review the eligibility requirements, available programs, required documents, and application procedure carefully before applying. https://scholarshipforphd.com/ntust-scholarship/
Scholarship for PhD
NTUST Scholarship 2027 in Taiwan | Fully Funded without IELTS
Apply for the fully funded NTUST Scholarship 2027 in Taiwan for Master’s & Ph.D. degrees. No IELTS required. Study at Taiwan Tech in English-taught progra
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