Students will be introduced to the foundational concepts and applications of biostatistics in the field of public health. This course will provide an overview of various statistical methods used in public health practice and research, with a strong emphasis on the appropriate application of these methods and the interpretation of the results. Examples and problems from real-world public health settings will be included to reinforce the practical relevance of the material. Students will have the opportunity to work with various statistical software, such as Excel, STATA, JASP, and others, to analyze public health data, even if they have limited prior computing experience. The course aims to equip graduate students in public health with the essential knowledge and skills required for the collection, management, visualization, and analysis of public health data. Key concepts in statistical inference and hypothesis testing will be covered, including methods for summarizing data, estimation techniques, and hypothesis testing procedures such as the t-test, the chi-square test, the analysis of variance, correlation analysis, and linear regression.