Statistical techniques are crucial in scientific research as they facilitate the systematic gathering, structuring, analysis, interpretation, and presentation of data. These methods convert raw data into valuable insights and underpin evidence-based decision-making. This review paper outlines essential statistical methods employed in various research domains, such as descriptive statistics, which condense data, and inferential statistics, which enable conclusions about populations based on sample data. It also emphasizes significant techniques like regression analysis and hypothesis testing, commonly used to explore relationships between variables and verify research hypotheses. Additionally, the paper examines emerging strategies like machine learning and Bayesian analysis for managing complex datasets. The importance of sound research design, including sample selection and bias management, is stressed to ensure precision and dependability. In summary, statistical methods are indispensable for generating valid, reliable, and reproducible research results across different fields.
Miss. Mane Mukta Nanaso (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: