Oct 26th 2015

Statistical Reasoning for Public Health: Estimation, Inference, & Interpretation (Coursera)

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A conceptual and interpretive public health approach to some of the most commonly used methods from basic statistics.

In this data centric era, statistics has become an essential tool for processing information from the realm of public health and medical research. Understanding both the implications and limitations of the results from such research is essential for making informed treatment decisions, public health practice protocols and policy recommendations. In this class, a conceptual and interpretive approach is applied to some of the most used methods from basic statistics. The course will detail appropriate summary measures for quantifying the health of single populations, and comparing such outcomes between populations using results from representative but imperfect data samples. Additionally, the role of uncertainty in sample based estimated will be covered, allowing for conclusions to be drawn regarding the larger populations under study while recognizing the imperfection in the study estimates. All topics will be considered through a “conceptual lens” allowing students to focus on the “what”, “why”, and “so what” with regards to the implications of research results.