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Biostatistics and Data Science is an interdisciplinary field that combines the principles of statistics, computing, and domain-specific knowledge to analyze and interpret complex biological and medical data. It plays a critical role in evidence-based decision-making across health sciences, epidemiology, genetics, public health, and clinical research.

Biostatistics focuses on the design of biological experiments, the collection and analysis of data, and the interpretation of results in biomedical research. It includes descriptive and inferential statistics, hypothesis testing, regression analysis, and survival analysis. These statistical methods ensure that scientific conclusions are reliable and reproducible.

Data Science integrates statistical analysis with computer science, machine learning, and big data technologies to extract insights from large datasets. In the health domain, it supports applications such as disease prediction, personalized medicine, health informatics, and public health surveillance.

Together, biostatistics and data science enable professionals to handle real-world health data, identify patterns, test hypotheses, and develop predictive models that can inform clinical practices, public health policies, and biomedical innovations.