The Educational Research and Evaluation (ERE) Laboratory of the Graduate School of Universitas Negeri Yogyakarta (GS UNY), in collaboration with the Master and Doctoral Programs in Educational Research and Evaluation, once again organized ERE Lab Series #7 as part of its ongoing commitment to strengthening statistical data analysis competencies among academics and the general public.

Held under the theme “Upgrading Statistical Data Analysis Skills Using Free and Powerful Software: JAMOVI,” the program was conducted online via Zoom in three sessions on 14, 18, and 21 November 2025, starting at 7:00 PM (WIB).

The program was officially opened by the Director of GS UNY, who emphasized the importance of data analysis literacy in improving research quality and supporting evidence-based decision-making. The opening session was followed by a program report delivered by the Coordinator of the Master Program in ERE, who highlighted that the ERE Lab Series is a regular academic agenda aimed at strengthening participants’ methodological capacity.

The training featured Dr. Ezi Apino, M.Pd., Expert of the ERE Laboratory at GS UNY, as the main speaker. He provided comprehensive guidance on the use of JAMOVI, a free yet powerful statistical software recognized for its intuitive interface and broad applicability in quantitative data analysis.

The training materials included:

• Session 1 (14 November 2025): t-test, Correlation, and Regression
• Session 2 (18 November 2025): One- and Two-Way ANOVA and ANCOVA
• Session 3 (21 November 2025): One- and Two-Way MANOVA and MANCOVA

Participants came from diverse backgrounds, including alumni, lecturers, teachers, undergraduate and graduate students, researchers, practitioners, and educational staff from schools, universities, government institutions, and professional organizations.

High enthusiasm was reflected in active discussions that continued until 11:00 PM (WIB), demonstrating participants’ strong engagement and curiosity regarding statistical analysis topics presented during the sessions.

Through collaboration between the ERE Laboratory and the Master and Doctoral Programs in ERE, ERE Lab Series #7 is expected to further enhance research quality, expand academic networks, and strengthen data analysis competencies across various disciplines.