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Statistics — 2025, Undergraduate
This study designed a factorial experiment design and analysis tool that helps students and field researchers plan experiments and analyse results using ANOVA. The tool generates randomised layouts for common designs and computes main effects and interactions. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Flask, Statsmodels, and SQLite. The findings showed that the tool reduced design errors and supported correct interpretation of interaction effects, while achieving a high System Usability Scale score. The study recommends adoption in experimental design courses and agricultural research.
For reference and learning only. Do not submit this work as your own.

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