Statistical Analysis with R for Public Health, Short Course | Part time online | Coursera | United States
1 months
Duration
Free
Free
Unknown
Tuition fee
Anytime
Unknown
Apply date
Anytime
Unknown
Start date

About

In this Statistical Analysis with R for Public Health Specialization offered by Coursera in partnership with Imperial College London, you’ll take a peek at what medical research is and how – and indeed why – you turn a vague notion into a scientifically testable hypothesis. 

Visit the Visit programme website for more information

Overview

Statistics are everywhere. The probability it will rain today. Trends over time in unemployment rates. The odds that India will win the next cricket world cup. In sports like football, they started out as a bit of fun but have grown into big business. Statistical analysis also has a key role in medicine, not least in the broad and core discipline of public health.

You’ll learn about key statistical concepts like sampling, uncertainty, variation, missing values and distributions. Then you’ll get your hands dirty with analysing data sets covering some big public health challenges – fruit and vegetable consumption and cancer, risk factors for diabetes, and predictors of death following heart failure hospitalisation – using R, one of the most widely used and versatile free software packages around.

This specialisation consists of four courses – statistical thinking, linear regression, logistic regression and survival analysis – and is part of our upcoming Global Master in Public Health degree, which is due to start in September 2019.

The Statistical Analysis with R for Public Health Specialization offered by Coursera in partnership with Imperial College London can be taken independently of the GMPH and will assume no   knowledge of statistics or R software. You just need an interest in medical matters and quantitative data.

Applied Learning Project

In each course, you'll be introduced to key concepts and a data set to be used as a worked example throughout that course. Public health data are messy, with missing values and weird distributions all too common. The data you'll use are either real or simulated from real patient-level data sets (all anonymised and with usage permissions in place).

The emphasis will be on “learning through doing” and “learning through discovery” as you encounter typical data and analysis problems for you to solve and discuss among your fellow learners. You'll get the chance to work things out for yourself and with your peers before accessing the answers and explanation provided by the instructors. 

Programme Structure

Courses include:

  • Statistics & Data Analysis in Public Health
  • Linear Regression in R for Public Health
  • Logistic Regression in R for Public Health
  • Survival Analysis in R for Public Health

Key information

Duration

  • Part-time
    • 1 months
    • 10 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Academic requirements

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

Beginner Level

  • Familiarity with seeing graphs and tables. Basic numeracy (so NOT calculus, trigonometry etc). No medical, statistical or R knowledge is assumed.

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 months.
  • National

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

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.

Other interesting programmes for you

Our partners

Statistical Analysis with R for Public Health
-
Coursera

Wishlist

Go to your profile page to get personalised recommendations!