Learn public statistics and develop data analysis skills with R. Improve your statistical thinking and learn key data analysis methods with R.
Suggested by: Coursera (What is Coursera?)
No prior knowledge required
No unnecessary risks
Statistics are everywhere. The odds of today’s shooting. Time trends in unemployment rates. The odds of India winning the next Cricket World Cup. In sports like football, it started as a bit of fun but has evolved into big business. Statistical analysis also plays a major role in medicine, especially in the broad and core field of public health.
In this internship, you will help understand what medical research is and how – and why – a vague idea is transformed into a scientifically testable hypothesis. You will learn about key concepts in statistics such as:
Next, you will work on analyzing a data set that addresses several key public health challenges:
All this using R, one of the most free and widely used programs.
The specialization consists of four courses:
And it is part of the Global Master’s Program in Public Health that is scheduled to begin in September 2019.
The specialization can be studied independently from the MPH and does not require prior knowledge of statistics or R software. All you need is an interest in medical topics and quantitative data.
In each course, you will be exposed to key concepts and a dataset that will be used as an example throughout the course. Public health data can be messy, with missing values and strange distributions. The data that Kullan uses is either real or simulated from real patient data (all data is anonymized and with permission to use).
The emphasis will be on “learning by doing” and “learning by discovery” as you encounter typical data and analysis problems that you must solve and discuss with other learners. You will have the opportunity to work on the solutions yourself and with your peers before receiving the answers and explanations from the instructors.
