Looking at the two leading contenders, Mittens and Bolsharack, I have this evaluation on how good or bad each would be as the next POTUS. I'm trying in my mind to only evaluate each prospectively without holding past sins/virtues against/for them. That doesn't mean without thought to past performance as that is the leading source of thought toward projection. Keep in mind that the categories "Great" and "Awful" are highly selective company among past presidents. In each case I'm assuming the respective candidate wins election. Notice I include a 95% confidence interval around each.
Probabilities
Category: for Mittens to be: for Bolsharack to be:
Great 5% (+/- 3%) 3% (+/- 1%)
Good 15% (+/- 10%) 15% (+/- 10%)
Middling 50% (+/- 15%) 35% (+/- 15%)
Bad 25% (+/- 10%) 35% (+/- 10%)
Awful 10% (+/- 5%) 12% (+/- 5%)
These expectations are valued against how good a U.S. president reasonably should be within the circumstances of the politics of the day. Obviously, the actions of Congress and to a lesser extent geopolitical events play a large role in determining the potential a president can reach and the opportunities to achieve either extreme.
Wednesday, September 5, 2012
The Revolution Will Be Free and Online
The super heroes from Marginal Revolution have begun a new and exciting endeavor. They are launching a free, online economics university. From their website:
That’s Marginal Revolution University, MRU, or I suppose to some “Mister” University.
We think education should be better, cheaper, and easier to access. So we decided to take matters into our own hands and create a new online education platform toward those ends. We have decided to do more to communicate our personal vision of economics to you and to the broader world.
You can visit www.MRUniversity.com here. There you can sign up for information about our first course, Development Economics, which is described by Alex below.
Here are a few of the principles behind MR University:
1. The product is free (like this blog), and we offer more material in less time.
2. Most of our videos are short, so you can view and listen between tasks, rather than needing to schedule time for them. The average video is five minutes, twenty-eight seconds long. When needed, more videos are used to explain complex topics.
3. No talking heads and no long, boring lectures. We have tried to reconceptualize every aspect of the educational experience to be friendly to the on-line world.
4. It is low bandwidth and mobile-friendly. No ads.
5. We offer tests and quizzes.
6. We have plans to subtitle the videos in major languages. Our reach will be global, and in doing so we are building upon the global emphasis of our home institution, George Mason University.
7. We invite users to submit content.
8. It is a flexible learning module. It is not a “MOOC” per se, although it can be used to create a MOOC, namely a massive, open on-line course.
9. It is designed to grow rapidly and flexibly, absorbing new content in modular fashion — note the beehive structure to our logo. But we are starting with plenty of material.
10. We are pleased to announce that our first course will begin on October 1.
Saturday, September 1, 2012
A New Hope, the rebels are organizing
Warren Zola of The Sports Law Blog brings good news in the struggle for justice against the mighty NCAA cartel. The plaintiffs in the O'Bannon vs. NCAA case have moved to have their case certified as a class action and seek to have the damages used to pay college athletes via trusts. I feel a disturbance in the force...
Thursday, August 30, 2012
Required listening
Econtalk's latest: sports economist Roger Noll.
Perhaps no other field of application demonstrates the unique and powerful perspective of the economic way of thinking than does sports economics.
Perhaps no other field of application demonstrates the unique and powerful perspective of the economic way of thinking than does sports economics.
Wednesday, August 29, 2012
When you don't go to the polls this November . . .
Gene Healy writing at Reason.com reminds us why not to support the political party.
Stats without baselines
I was listening to NPR this morning and near the end of Marketplace Morning Report came a common error seen and heard all too often: statistics that seemingly impart deep meaning but in fact are meaningless because we lack a reference point from which to judge them.
The specific occurrence in this case was a brief comment on Allstate Insurance's latest release of its annual report, "Allstate America's Best Drivers Report". The two snippets were that Philadelphia drivers were 64% more likely to be in a collision than the average driver nationally and that the safest drivers are in Sioux Falls, South Dakota where drivers on average go 14 years between collisions. The actual official report is here.
Besides the problems with how each statement is worded as compared to what those statistics are actually saying (I may have the quotes wrong as well), there is the bigger concern, for me at least, that we really don't know if those numbers are in any way significant. To know that we'd need to know more about the full data set including the actual averages and dispersion. We'd also probably like to know how volatile these statistics are year after year and how they were computed. But we don't know any of that from the report; so all we are left with are the impressions they make at first glance, which are highly subject to personal bias and incorrect interpretation. We'd also like to know if the statistics are adjusted for factors such as miles driven and conditions like weather (they are not).
But thinking about both numbers together we can cobble together a little logic to help know that they are probably not significant numbers. It would be highly unlikely that drivers in Sioux Falls or any other city are that different any other American city. At 14 years between collisions, collisions seem pretty rare. Rare events can be easily distorted by slight adjustments in contributing factors including random factors. A 64% increase over average is therefore probably not statistically significant. For those in the City of Brotherly Love, I say, drive on.
The specific occurrence in this case was a brief comment on Allstate Insurance's latest release of its annual report, "Allstate America's Best Drivers Report". The two snippets were that Philadelphia drivers were 64% more likely to be in a collision than the average driver nationally and that the safest drivers are in Sioux Falls, South Dakota where drivers on average go 14 years between collisions. The actual official report is here.
Besides the problems with how each statement is worded as compared to what those statistics are actually saying (I may have the quotes wrong as well), there is the bigger concern, for me at least, that we really don't know if those numbers are in any way significant. To know that we'd need to know more about the full data set including the actual averages and dispersion. We'd also probably like to know how volatile these statistics are year after year and how they were computed. But we don't know any of that from the report; so all we are left with are the impressions they make at first glance, which are highly subject to personal bias and incorrect interpretation. We'd also like to know if the statistics are adjusted for factors such as miles driven and conditions like weather (they are not).
But thinking about both numbers together we can cobble together a little logic to help know that they are probably not significant numbers. It would be highly unlikely that drivers in Sioux Falls or any other city are that different any other American city. At 14 years between collisions, collisions seem pretty rare. Rare events can be easily distorted by slight adjustments in contributing factors including random factors. A 64% increase over average is therefore probably not statistically significant. For those in the City of Brotherly Love, I say, drive on.
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