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

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

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24 Articles
A jellyfish
Oct 18, 2022
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
Sep 09, 2022
Ordinal data is any data that can be ranked or ordered. How does it differ from other types?
A woman sleeps at a desk piled with paperwork, coffee cups, and other detritus
Aug 09, 2022
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
Jun 14, 2022
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.
Apr 05, 2022
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
Feb 22, 2022
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
Jan 11, 2022
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
Nov 16, 2021
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.
Sep 21, 2021
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.
Aug 10, 2021
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.
Jul 12, 2021
Tech companies often prefer job candidates with majors in STEM fields in their hiring practices. The day-to-day reality of the workplace, however, suggests they would be better served to focus on a different set of criteria.
Jun 04, 2021
Although researchers often spend little time discussing data preparation, it has the potential to massively alter a given study’s results. To ensure research remains useful, we need universal standards and better documentation.