Population Health: Responsible Data Analysis
About this course
In most areas of health, data is being used to make important decisions. As a health population manager, you will have the opportunity to use data to answer interesting questions. In this course, we will discuss data analysis from a responsible perspective, which will help you to extract useful information from data and enlarge your knowledge about specific aspects of interest of the population. First, you will learn how to obtain, safely gather, clean and explore data. Then, we will discuss that because data are usually obtained from a sample of a limited number of individuals, statistical methods are needed to make claims about the whole population of interest. You will discover how statistical inference, hypothesis testing and regression techniques will help you to make the connection between samples and populations. A final important aspect is interpreting and reporting. How can we transform information into knowledge? How can we separate trustworthy information from noise? In the last part of the course, we will cover the critical assessment of the results, and we will discuss challenges and dangers of data analysis in the era of big data and massive amounts of information. In this course, we will emphasize the concepts and we will also teach you how to effectively perform your analysis using R. You do not need to install R on your computer to follow the course, you will be able to access R and all the example data sets within the Coursera environment. This course will become part of the to-be-developed Leiden University master program Population Health Management. If you wish to find out more about this program see the last reading of this Course!
96/100
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What you'll learn
- Obtain, gather, clean, and explore health data safely and systematically
- Apply statistical inference methods to make claims about populations based on sample data
- Perform hypothesis testing and regression analysis for population health questions
- Conduct data analysis using R programming language
- Critically assess analysis results and distinguish trustworthy information from noise
- Interpret and report data findings responsibly in the context of big data challenges
Course objectives
- Develop responsible data analysis practices for population health management
- Master the connection between sample data and population-level conclusions using statistical methods
- Transform health data into actionable knowledge while understanding the limitations and dangers of big data analysis
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