IFST2BR: An Interpretive Framework for Statistical Tests Aimed at Budding Biological Researchers
Year: 2025
Type: article
Abstract: A statistical test is a formal method used in data analysis to make inferences, identify relationships, and draw conclusions about a population based on sample data. Many emerging biological researchers face challenges in managing their statistical findings because they often lack clear guidelines or interpretive frameworks to help them navigate their research safely. If a researcher fails to use the correct statistical test, the results may be harmful, and the conclusions could be unclear and misleading. It is essential to have an interpretive framework that guides and assists novice biological researchers in selecting and interpreting their statistical data. In this paper, an interpretive framework for statistical tests for emerging biological researchers was proposed. The proposed framework IFST2BR was validated through expert reviews and focus group discussions in terms of relevancy and understanding. After validation, the results obtained demonstrated the practical usability of the proposed framework as a guide and assistant for emerging biological researchers.
Author: Shahad Dakhil Khalaf
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409616984