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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- 1 star0.30%
来自SIMPLE REGRESSION ANALYSIS IN PUBLIC HEALTH 的热门评论
I would consider this an intuitive introduction to linear regression as a powerful statistical tool. The use of data from real studies is also a nice touch.
I really enjoyed learning this course. Very informative. Thanks a lot.
Very practical course. The tutor makes complex concepts seem easy.
This course covers all types of Simple Regressions. Instructor explained the complex topics in simple language. Relevant examples from clinical field and thorough explanation by the Instructor.