From Charles Stewart on Twitter via Brendan Nyhan: vote by county
Republicans.
Yes, from a campaign-strategy and political-science point of view there are important small changes that (together with Electoral College bias) explain why Clinton lost and Obama won. Yes, Clinton won noticeably fewer votes in small counties, and this matters. But, to first order, the same people voted for Trump as for Romney.
(more detailed graphs here)
(To be updated as they turn up)
(Nominated by James Green in comments: 538’s ‘winding path’)
Recommendations for sites to watch
First, ABC News exit poll doesn’t seem to understand bar charts
The chance of winning Powerball on a usual Lotto draw is fairly easy to calculate: you need pick 6 numbers correctly out of 40, and the powerball number correctly out of 10. The number of possible combinations is 3,838,380×10=38,383,800, so your chance is 1 in 38,383,800. Buying 10 combinations twice a week, you’d get a perfect match a bit more than once every 37,000 years.
On Saturday, the prize was $38 million dollars. If tickets were $1 or less, the big prize would pay for buying all 38 million combinations — and the expected value of even smaller numbers of tickets would be more than they cost. However, tickets cost $1.20 per “line” ($0.60 for the six numbers, $0.60 for the Powerball), so you’d still lose money on average with each ticket you buy.
‘Must Win’ jackpots like the one on Wednesday are different. The $40 million prize has to go, so the expected prize value per “line” is $40 million divided by the number of lines sold. Unfortunately, we don’t know what that number is. For the last ‘Must Win’ jackpot there were 2.7 million tickets sold, but we don’t know how many lines that represents; the most popular ticket has 10.
It looks like the expected value of tickets for this draw might be positive. However ‘expected value’ is a technical term that’s a bit misleading in English: it’s the average (mean) of a lot of small losses and a few big wins. Almost everyone who buys tickets for Wednesday’s draw will miss out on the big prize — the ‘averages’ don’t start averaging out until you buy millions of tickets. Still, your chances are probably better than in usual weeks.
Each week, we would like to invite readers of Stats Chat to submit nominations for our Stat of the Week competition and be in with the chance to win an iTunes voucher.
Here’s how it works:
Next Monday at midday we’ll announce the winner of this week’s Stat of the Week competition, and start a new one.
If you’d like to comment on or debate any of this week’s Stat of the Week nominations, please do so below!
This one’s from the New England Journal of Medicine, who tweeted
If this graph conveyed any information, it would be saying the new trial of anti-retroviral treatment found no difference in neonatal HIV infection rates. Fortunately, the tweet is just clickbait, and if you click on the link (not the picture) and wait through a minute and a half of video, you get the real graph
You could also just read the abstract of the paper to get the information more quickly.
(via Julian Wolfson)
We’ve known since at least the 1980s that there’s a problem with clinical trial results not being published. Tracking the non-publication rate is time-consuming, though. There’s a new website out that tries to automate the process, and a paper that claims it’s fairly accurate, at least for the subset of trials registered at ClinicalTrials.gov. It picks up most medical journals and also picks up results published directly at ClinicalTrials.gov — an alternative pathway for boring results such as dose equivalence studies for generics.
Here’s the overall summary for all trial organisers with more than 30 registered trials:
The overall results are pretty much what people have been claiming. The details might surprise you if you haven’t looked into the issue carefully. There’s a fairly pronounced difference between drug companies and academic institutions — the drug companies are better at publishing their trials.
For example, compare Merck to the Mayo Clinic
It’s not uniform, but the trend is pretty clear.
Q: So, lots of good health news today!
A: <suspiciously> Yes?
Q: Eating tomatoes prevents wrinkles and skin cancer! And it’s going to be tomato season soon.
A: Not convinced
Q: Why? Did the people have to eat too many tomatoes? Is that even possible?
A: No tomatoes were involved in the study. People took capsules of oil with tomato extract high in lycopene or lutein.
Q: Sounds a bit of a waste. But still, reducing wrinkles and sun damage generally must be good.
A: They didn’t measure wrinkles or skin cancer either.
Q: So what did they measure?
A: Activity of some genes related to skin damage by ultraviolet light.
Q: And these were significantly reduced, right?
A: Yes, but ‘significantly’ here just means ‘detectably’. It doesn’t necessarily translate into a lot of protection.
Q: Do they have an estimate of how much protection?
A: The Herald story says an earlier study found taking lycopene supplements to be as effective as an SPF 1.3 sunscreen.
Q: Only SPF 13? Still, if that’s just from the supplement it’s pretty impressive.
A: Not 13. SPF 1.3.
Q: Ok, so that’s not so impressive. But tomato season and sunscreen season peak at the same time, and every bit helps.
A: Actually, if it really is the lycopene, your horiatiki salad isn’t going to work — lycopene isn’t well absorbed from fresh tomatoes.
The headlines at both the Herald and Stuff say they’re about Lotto winners, but the vastly more numerous losers have to have basically the same demographics. That means any statistics drawn from a group of 12 winners are going to be very unreliable.
There some more reliable sources. There’s (limited) information released by NZ Lotteries under the Official Information Act. There’s also more detailed survey data from the 2012 Health and Lifestyles Survey (PDF)
Of the 12 people in today’s stories, 11 were men, even though men and women play Lotto at about the same rate. There’s a lot less variation by household income than I would have guessed. There is some variation by ethnicity, with Asians being less likely to play Lotto. People under 25 are a bit less likely to play. It’s all pretty boring.
I’ve complained a few times that clicky bogus polls have an error rate as bad as a random sample of about ten people, and are useless. Here we have a random sample of about ten people, and it’s pretty useless.
Except as advertising.