Posts filed under General (3156)

From Slate

From the New York Times:

Statistical analysis has swept through baseball over the past decade, becoming part of the fabric of the game and an object of growing fascination to its fans. As players, managers and front office executives embrace the esoteric statistics, teams increasingly want their radio announcers just as fluent in the language of WAR, VORP and B.A.B.I.P.

Say what?

Read the full story here.

Team Ratings for Round 5

Here are the team ratings prior to Round 5, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 12 matches played, 5 of which were correctly predicted, a success rate of 41.7%.

Here are the predictions for last week’s games.

Predictions for Round 5

Here are the predictions for Round 5. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 26

Here are the team ratings prior to Round 26, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Performance So Far

So far there have been 184 matches played, 112 of which were correctly predicted, a success rate of 60.87%.

Here are the predictions for last week’s games.

Predictions for Round 26

Here are the predictions for Round 26. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

In the run up to the US election, there was a popular factoid to the effect that  50% of the US population paid no tax. This was, of course, untrue, but it could be arrived at by minor blurring of a true statement:  47% of tax units (family or individual) paid no net federal income tax.   The US has a strongly progressive federal income tax (more so than NZ), combined with a moderately regressive federal payroll tax and state and local taxes.  The average tax rate ranges from 17% for the poorest 20% of people, to 25% for the middle 20%, to 29% for the richest 1%. These figures are potentially misleading in the other direction, since they don’t count benefits, but the US benefit system is relatively limited and the figures for the middle 20% and up would not be appreciably different.

Doing this sort of calculation precisely is surprisingly difficult, because it’s not as easy as you might think to work out who really pays which taxes.  For example, you might assume that shoppers pay GST and land owners pay land taxes/rates, but in fact renters end up paying a chunk of the rates in increased rent, and retailers pay a small part of GST in reduced profits.   In New Zealand it’s probably a reasonable approximation to just count income tax and GST, and to assume these are effectively paid by earners and buyers.  It’s not a reasonable approximation to just count income tax — and publishing estimates of tax share that only use income tax and benefits, even if you do it with scrupulous accuracy, is likely to lead to the sort of misquotation that we saw in the US.

Over at pundit.co.nz, Rob Salmond does some calculations, and while I think the tone is unnecessarily inflammatory, the final numbers look plausible. The 10% highest-income households  get about 30% of the income and they (actually, ‘we’, I think) pay 43% of the net tax.  [Rob also mentions the highest-wealth 10% of families, implying incorrectly that these are the same people].

For comparison, in the US, it’s the highest-income 5% of the population that gets 35% of the income and they pay 37% of the tax. Since benefits are about 28% of US federal spending, they are about 18% of all taxes, and so the share of net taxes for the top 5% will be about 44%. NZ is both less unequal and has a slightly more progressive tax and transfer system (and we have a national health system, too).  In the other direction, we have more inequality and a less progressive tax and transfer system than, say, Sweden.

If we stipulate that a mix of income tax and GST, with few deductions, is what we’re working with, making the  tax system more progressive has obvious benefits in terms of reducing inequality, and costs in terms of reducing productivity.  Making this tradeoff is a policy issue rather than a technical one, and it’s perfectly reasonable for people to argue for their own positions as strongly as they can: inequality and productivity are worth arguing about.

On the other hand, if you’re going to use a relatively unnatural statistic based on income tax and benefits but not GST, aggregated in an unusual way, I think you have the responsibility to point out carefully  and explicitly that you’ve left out GST (and, ideally, explain why). Bill English said ” The 1.3 million households with incomes under $110,000 a year collectively pay no net tax—that is, their total income support payments match their combined income tax.” The clause before the dash is simply false. The clause after the dash is true, but I don’t think it’s a contribution to informed public debate.

Team Ratings for Round 25

Here are the team ratings prior to Round 25, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Performance So Far

So far there have been 176 matches played, 108 of which were correctly predicted, a success rate of 61.36%.

Here are the predictions for last week’s games.

Predictions for Round 25

Here are the predictions for Round 25. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

This is proving to be an extremely unpredictable competition. The Lions absolutely thrashing the Bulls last weekend has resulted in a rankings jump for the Lions and a drop for the Bulls. Certainly the competition is harder to predict than the Australian NRL which in turn is harder to predict than the Super 15.

Team Ratings for Round 4

Here are the team ratings prior to Round 4, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 9 matches played, 3 of which were correctly predicted, a success rate of 33.3%.

Here are the predictions for last week’s games.

Predictions for Round 4

Here are the predictions for Round 4. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Oh dear, mea culpa. I was alerted by Pierre du Plessis (pduplessis1@gmail.com) that my predictions were a bit bizarre and on checking I found I had entered an incorrect parameter value. Here are the correct predictions for this week. Note that the success probability below is what would have been obtained if I had entered the correct parameter value previously.
 

Team Ratings for Round 3

Here are the team ratings prior to Round 3, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 6 matches played, 3 of which were correctly predicted, a success rate of 50%.

Here are the predictions for last week’s games.

Predictions for Round 3

Here are the predictions for Round 3. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 24

Here are the team ratings prior to Round 24, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Performance So Far

So far there have been 168 matches played, 103 of which were correctly predicted, a success rate of 61.31%.

Here are the predictions for last week’s games.

Predictions for Round 24

Here are the predictions for Round 24. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Diversity edition

• Statistical classification (data mining, learning) algorithms will learn to match your classifications. Sometimes that’s not quite what you want
• People are starting to comment more on entirely-male conference speaker lineups. Here’s a simple calculator for the probability distribution of number of people from some group (eg women), for a given proportion in the target population. For example, if you select 10 people from a population that’s 15% female, you should have only a 1/9 chance of not getting any women.
• Map of scientific collaborations, based on co-authorship of books and papers. (click for a really big version)