Foundations of Statistics for Public Health Analysis

Public health relies on accurate data interpretation to improve community outcomes and guide policy. This course provides a solid grounding in statistical methods, enabling you to explore raw datasets, identify patterns, and draw meaningful conclusions from health-related information. You will move from understanding basic terminology to performing inferential statistics that inform real-world health interventions. By the end of this course, you will be able to approach an unfamiliar dataset and confidently describe its features while testing specific research questions. What you'll learn: - Understand the fundamental types of variables and common probability distributions used in health research - Analyze raw health datasets to identify key features, trends, and potential outliers - Apply hypothesis testing techniques to compare means and proportions across different populations - Calculate and interpret confidence intervals and p-values within a public health context - Practice ethical data handling and understand the importance of reproducible research practices The course begins with essential terminology and statistical theory before moving into practical data exploration and inferential techniques. You will learn to formulate research questions and validate them using rigorous mathematical foundations through written examples and exercises. This course is designed for beginners in public health, social sciences, or healthcare administration with no prior statistical experience required. Start building your analytical skills for public health today.