Edward Hearn
Economist at Intensity, LLC
Expertise: Big data, data science
Education: Vanderbilt University; University of North Carolina, Charlotte; University of Georgia

Edward Hearn is an economist for Intensity, LLC, with specializations in data science, workforce analytics and human capital modeling.

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26 Articles
A hand prepares to flip a coin
The words likelihood and probability are often used interchangeably, but they actually refer to two distinct types of measurement. Our expert explains the difference in detail here.
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Creative Commons licenses are a new legal tool aimed at bringing copyright law into the digital age. Here, our expert explains how they work and weighs their pros and cons.
A jellyfish
Stratified sampling is a method of data collection that offers greater precision in many cases. This guide introduces you to its methods and principles.
A woman measures a child's height against the wall
Ordinal data is any data that can be ranked or ordered. How does it differ from other data types?
A woman sleeps at a desk piled with paperwork, coffee cups, and other detritus
Scope creep is a pernicious problem that can spike a budget and tank a project. Solving it before it begins is your best bet.
A data science team discusses their work
Too often, sloppy research methods return results that are mathematically supported but in no way reflect reality. To fix this problem, incorporate context in the form of prior assumptions.
A table with researchers using charts, a tablet, and laptop.
Data-driven research is crucial to understanding the marketplace, yet the replication crisis suggests much big-data analysis may be worthless. Fortunately, a simple tweak to research methods can undo much of the harm.
An adventurer jumps from one rock outcropping to another
To make effective risk assessments, you need to understand the difference between relative and absolute risk.
A woman works at a computer with a big data overlay
The proliferation of AI solutions has made big data all the rage, but you can probably find a less expensive way to generate useful, actionable insights.
A data analyst gives a presentation to communicate findings
You can compile all the data-driven analysis you like, but it’s useless unless someone in a position of power actually pays attention to it. Make sure you include the key ingredient to pique interest: context.
Despite astonishing technological breakthroughs, productivity has been relatively stagnant over the past two decades. Sussing out the reason for this stagnation offers a useful blueprint for future corporate investment.
A problem from econometrics illustrates the difference between artificial and human intelligence. Understanding tacit knowledge and the limits of AI is crucial to deploying it effectively and fairly.