Biostatistics is the application of statistical reasoning to the life sciences, and it's the key to unlocking the data gathered by researchers and the evidence presented in the scientific public health literature. In this course, we'll focus on the use of simple regression methods to determine the relationship between an outcome of interest and a single predictor via a linear equation. Along the way, you'll be introduced to a variety of methods, and you'll practice interpreting data and performing calculations on real data from published studies. Topics include logistic regression, confidence intervals, p-values, Cox regression, confounding, adjustment, and effect modification.
The recommended math prerequisite is up through and including basic algebra including logarithms and the equation of a line.
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來自SIMPLE REGRESSION ANALYSIS IN PUBLIC HEALTH 的熱門評論
I really enjoyed learning this course. Very informative. Thanks a lot.
Another exceptional class by Dr. John McGready. Clear and concise with many real-world research reviews that make challenging subjects such as logistic regression much more easy to understand.
Thank you so much for a beautiful explanation and presentation of topics that a lot of physicians tend struggle with, by making it understandable and logical
It would have been helpful to make regression exercises in a computer program. The acquired knowledge is theoretical and not practical, nonetheless it was a good course in general.