Pop quiz: which of the following statements about decisions do you agree with:
- You need at least thirty data points to get a statistically significant result.
- One data point tells you nothing.
- In a business decision, the monetary value of data is more important than its statistical significance.
- If you know almost nothing, almost anything will tell you something.
Ilya Pozin has written an article on inc.com that discusses how to be more efficient in a project and how to ensure that your team knows what success should look like. This article gives a good way to decompose aspects of project success, but I found myself thirsting for quantitative measures.
The author mentions six factors for measuring the success of a project: (more…)
It has been a heck of a winter for Portland, OR. The city has had nine school closure days due to snow and other winter weather. Per local reports, the metro area has been effectively shut down on many of these days. Portland’s transportation bureau budgets $300K a year for materials to respond to winter storms, and has 55 snowplows. In contrast, Portland’s GDP is $160 B/year which translates to $635 MM per work day.
At first blush, there is an intuitive sense that spending a fraction of a percent of one day’s GDP is going to be less than the optimal amount, but there are some mitigating factors. (more…)
Given the current pricing of wolf hunting licenses in Wisconsin, it is unlikely that revenue from the wolf licenses offset the negative effects wolves have from killing deer, livestock, and dogs. However, there are two caveats to this statement: first, to make this assessment definitive depends on accurately estimating the worth of the life of a deer in Wisconsin, and may depend on more accurately estimating the monetary equivalent loss for a family who has had a dog killed by a wolf. (more…)