Statistical Reasoning for Public Health 1: Estimation, Inference, and Interpretation is an online course offered by Johns Hopkins University. This course is a conceptual and interpretive approach to commonly used methods in the basic statistics involved in Public Health Epidemiology. Each module focuses on different techniques used when running statistical tests on epidemiological data, binary outcomes, time-to-event outcomes, and hypothesis testing. Other topics covered include sampling variability, confidence intervals, study design types, data types, and data summarization. This 8-week course requires between 7 and 9 hours of work a week to complete all course materials. Each module consists of a combination of videos and readings, with quizzes due periodically to assess individual’s understanding of the material. Those who pass all graded assignments will complete the course.