Abstract
Statistical methods are integral to biological research, enabling scientists to make data-driven decisions, validate hypotheses, and identify patterns in complex biological systems. From clinical trials and genomics to ecology and epidemiology, statistics provides a robust framework for data collection, analysis, and interpretation. This paper explores the diverse applications of statistical techniques in biological research, including descriptive and inferential statistics, regression modeling, hypothesis testing, and multivariate analysis. The integration of statistical tools enhances reproducibility, improves experimental design, and supports innovation in life sciences.
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