Statistical applications in the biomedical sciences: A review

This study covers applications areas of statistics in biological science. The integration of statistical methods into the biological sciences has revolutionized data analysis, enhancing the accuracy of data analysis and interpretation. This review aims to provide a comprehensive overview of the key statistical techniques used in biomedical research, highlighting their applications, advantages, and limitations. We conducted a systematic literature search across major databases, we focused on studies that have employed descriptive statistics, inferential statistics, regression analysis, multivariate analysis, survival analysis, Bayesian statistics, and machine learning methods in biomedical sciences. Our findings reveal that statistical methods are indispensable in various areas, including genomics, proteomics, epidemiology, ecology, clinical trials, and pharmacology. Each section of this review details the specific applications of these methods, supported by relevant case studies that illustrate their practical implementation and impact. This review underscores the indispensable role of statistics in biological research, providing actionable insights and recommendations for researchers aiming to leverage statistical tools to drive scientific discovery.