Lecture notes

• EDA/Charts
• Ubiquitous variation
• Parametric inference
• Probability Theory
• Odds Ratio/Relative Risk
• Distributions
• Exploratory data analysis
• Resampling/Simulation
• Design of Experiments
• Intro to Epidemiology
• Estimation
• Hypothesis testing
• Experiments vs. Observational studies
• Data management (tables, streams, cloud, warehouses, DBs, arrays, binary, ASCII, handling, mechanics)
• Power, sample-size, effect-size, sensitivity, specificity
• Bias/Precision
• Association vs. Causality
• Rate-of-change
• Clinical vs. Stat significance
• Statistical Independence Bayesian Rule

Note: The SMHS EBook is NOT intended to serve as a substitute for attending lectures. The information provided in the EBook is incomplete and insufficient, by itself, for learning the material in this course. This information is supplemental to the material presented in lectures, discussions and labs.