Logistic Regression in R for Public Health, Certificate | Part time online | Coursera | United States
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# Logistic Regression in R for Public Health

1 days
Duration
Free
Free
Unknown
Tuition fee
Anytime
Unknown
Apply date
Anytime
Unknown
Start date

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 Logistic Regression in R for Public Health course offered by Coursera in partnership with Imperial College London.

## Overview

#### Key Features

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. 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.

By the end of this course, you will be able to:

• Explain when it is valid to use logistic regression
• Define odds and odds ratios
• Run simple and multiple logistic regression analysis in R and interpret the output
• Evaluate the model assumptions for multiple logistic regression in R
• Describe and compare some common ways to choose a multiple regression model

This Logistic Regression in R for Public Health course offered by Coursera in partnership with Imperial College London builds on skills such as hypothesis testing, p values, and how to use R, which are covered in the first two courses of the Statistics for Public Health specialisation. If you are unfamiliar with these skills, we suggest you review Statistical Thinking for Public Health and Linear Regression for Public Health before beginning this course. If you are already familiar with these skills, we are confident that you will enjoy furthering your knowledge and skills in Statistics for Public Health: Logistic Regression for Public Health.

## Programme Structure

Courses include:

• Logistic Regression
• Logistic Regression in R
• Running Multiple Logistic Regression in R
• Assessing Model Fit

## Key information

• Part-time
• 1 days

### Start dates & application deadlines

You can apply for and start this programme anytime.

English

### Delivered

Online
• Self-paced

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

## English requirements

We are not aware of any English requirements for this programme.

## Other requirements

### General requirements

Intermediate Level

• You'll need to have taken the Statistical Thinking and Linear Regression courses in this series or have equivalent knowledge.

## Tuition Fee

To always see correct tuition fees
• ### International

Free
Tuition Fee
Based on the tuition of 0 USD for the full programme during 1 days.
• ### National

Free
Tuition Fee
Based on the tuition of 0 USD for the full programme during 1 days.

You can choose from hundreds of free courses, or get a degree or certificate at a breakthrough price. You can now select Coursera Plus, an annual subscription that provides unlimited access.

## Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.

## Our partners

Logistic Regression in R for Public Health
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