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Description

Why logistic regression for public health rather than just logistic regression? Well, there are some particular considerations for every data set, and public health data sets have particular features that need special attention. In a word, they're messy. Like the others in the series, this is a hands-on course, giving you plenty of practice with R on real-life, messy data, with predicting who has diabetes from a set of patient characteristics as the worked example for this course. Additionally, the interpretation of the outputs from the regression model can differ depending on the perspective that you take, and public health doesn’t just take the perspective of an individual patient but must also consider the population angle. That said, much of what is covered in this course is true for logistic regression when applied to any data set, so you will be able to apply the principles of this course to logistic regression more broadly too.Read more.

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Career Relevance by Data Role

The techniques and tools covered in *Logistic Regression in R for Public Health* are most similar to the requirements found in Data Scientist job advertisements.

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Learning Sequence

Logistic Regression in R for Public Health is a part of one structured learning path.

Coursera

Imperial College London

Specialization |
4 Courses
4 Months