Linear Regression in R for Public Health Coursera

Overview

Key Features

Public Health has been defined as “the art and science of preventing disease, prolonging life and promoting health through the organized efforts of society”. Knowing what causes disease and what makes it worse are clearly vital parts of this. This requires the development of statistical models that describe how patient and environmental factors affect our chances of getting ill. This Linear Regression in R for Public Health course offered by Coursera in partnership with Imperial College London will show you how to create such models from scratch, beginning with introducing you to the concept of correlation and  linear regression before walking you through importing and examining your data, and then showing you how to fit models. Using the example of respiratory disease, these models will describe how patient and other factors affect outcomes such as lung function. 

Linear regression is one of a family of regression models, and the other courses in this series will cover two further members. Regression models have many things in common with each other, though the mathematical details differ. 

You will use the free and versatile software package R, used by statisticians and data scientists in academia, governments and industry worldwide.