The accuracy of your IRRs and NPVs depends to a large extent on the quality of the assumptions that go into the financial model. However, there is one element that also affects the accuracy of the calculations.
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Many finance problems inherently involve circular calculations. The most common of them is balancing the balance sheet. So how do we typically solve such kind of modeling problems?
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In his brilliant book Beautiful Evidence, Edward Tufte—nicknamed the Leonardo da Vinci of data by The New York Times—introduced six principles that he calls the fundamental principles of analytical design.
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We've always been fascinated by the concept of “time”. It's probably the most important concept known to mankind and has long been a major subject of study in religion, philosophy, and science.
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DATA VISUALIZATION
FINANCIAL MODELING
BUSINESS MODELING
Adopted public policies affect everyone—they're called public for a reason after all. Nowhere is this truer than in the realm of defense policy.
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It’s useful to distinguish two types of average measures: Simple average (or arithmetic average) and weighted average. Both—simple and weighted averages—are widely used in practice but each type is more appropriate to use than the other for certain purposes and applications.
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If you ask a group of data analysts and data visualization experts to choose the most important chart type to display data, most probably “The scatterplot” would be the response you’ll get. And they have a point.
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Outside the realm of hard sciences, I generally follow a simple heuristic to identify books worth reading. 1) Read books that have been in print for 15 years or so. 2) Break rule #1 for books written by authors who have in their portfolio at least one book that passes rule #1.
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EXCEL CHARTS
When you look at correlation, when you hear correlation you’ve got to be suspicious. Learn how not to be fooled by relationships that are completely spurious.
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The Data-Ink ratio is a concept first introduced by Edward Tufte—in his book the Visual Display of Quantitative Information. It can be summarized—in Tufte’s own words—by the fundamental principle of statistical graphics: Above all else show the data.
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I pity tables. Most of us demote them to the bottom of the data visualization food chain—all too often for the wrong reasons. This is unfortunate because tables could be—in some instances—better than graphs at presenting information.
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Graphs are essential to good statistical analysis. Both summary statistics and graphs should be studied in any data analysis—since each will contribute to understanding.
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