Posts filed under Politics (129)

November 5, 2014

US election graphics

Facebook has a live map of who has mentioned on Facebook that they had voted (via Jason Sundram)

facebook-voted

USA Today showed a video including a Twitter live map

twitter-elections

These both have the usual problem with maps of how many people do something: there are more people in some places than others. As usual, XKCD puts it well:

xkcd-elections

Useful statistics is about comparisons, and this comparison basically shows that more people live in New York than in New Underwood.

As usual, the New York Times has informative graphics, including a live set of projections for the interesting seats.

 

November 3, 2014

It’s warmer out there

Following a discussion on Twitter this morning, I thought I’d write again about increasing global temperatures, and also about the types of probability statements.

The Berkeley Earth Surface Temperature project is the most straightforward source for conclusions about warming in the recent past. The project was founded by Richard Muller, a physicist who was concerned about the treatment of the raw temperature measurements in some climate projections. At one point, there was a valid concern that the increasing average temperatures could be some sort of statistical artefact based on city growth (‘urban heat island’) or on the different spatial distribution and accuracy of recent and older monitors. This turned out not to be the case. Temperatures are increasing, systematically.  The Berkeley Earth estimate agrees very well with the NASA, NOAA, and Hadley/CRU estimates for recent decades

best

The grey band around the curve is also important. This is the random error. There basically isn’t any.  To be precise, for recent years, the difference between current and average temperatures is 20 to 40 times the uncertainty — compare this to the 5σ used in particle physics.

What there is uncertainty about is the future (where prediction is hard), and the causal processes involved. That’s not to say it’s a complete free-for-all. The broad global trends fit very well to a simple model based on CO2 concentration plus the cooling effects of major volcanic eruptions, but the detail is hard to predict.

Berkeley Earth has a page comparing reconstructions of  temperatures with actual data for many climate models.  The models in the last major IPCC assessment report show a fairly wide band of prediction uncertainty — implying that future temperatures are more uncertain than current temperatures. The lines still all go up, but by varying amounts.

best-gcm

 

The same page has a detailed comparison of the regional accuracy of the models used in the new IPCC report. The overall trend is clear, but none of the models is uniformly accurate. That’s where the uncertainty comes from in the IPCC statements.

The earth has warmed, and as the oceans catch up there will be sea levels rises. That’s current data, without any forecasting.  There’s basically no uncertainty there.

It’s extremely likely that the warming will continue, and very likely that it is predominantly due to human-driven emissions of greenhouses gases.

We don’t know accurately how much warming there will be, or exactly how it will be distributed.  That’s not an argument against acting. The short-term and medium-term harm of climate changes increases faster than linearly with the temperature (4 degrees is much worse than 2 degrees, not twice as bad), which means the expected benefit of doing something to fix it is greater than if we had the same average prediction with zero uncertainty.

October 7, 2014

Enumerating hard-to-reach populations

I’ve written before about how it’s hard to get accurate estimates of the size of small subpopulations, even with large, well-designed surveys.

Via the Herald

Mr Key said that was an emerging issue for New Zealand. “If I was to spell out to New Zealanders the exact number of people looking to leave and be foreign fighters, it would be larger, I think, than New Zealanders would expect that number to be.”

If the government really knows the ‘exact number’, there must have been a lot more domestic surveillance than we’ve been told about.

New Zealanders probably don’t have any very well formed expectations for that number, since we have basically no information to go on. My guess would be along the lines of “Not very many, but people are strange,  so probably some.” I’d be surprised if it were less than 10 or more than 1000.

 

October 6, 2014

NZ voting cartograms

One of the problems with electoral maps is the ‘one cow, one vote’ effect: rural electorates are physically bigger, and so take up more of the map. When you combine that with the winner-take-all impact of simple colour schemes, it can look as though National won basically everything instead of just missing out on a majority.

Using a design by Chris McDowall that I linked earlier this year, David Friggens has mapped out the party votes across the country with equal area given to each electorate.  These maps show where the votes for each major party came from

big4

 

He also has maps for the minor parties, some of which have very localised support.

September 22, 2014

So, we had an election

Turnout of enrolled voters was up 3 percentage points over 2011, but enrollment was down, so as a fraction of the eligible population, turnout was only up half a percentage point.

From the Herald’s interactive, the remarkably boring trends through the count

There are a few electorates that are, arguably, still uncertain, but by 9pm the main real uncertainty at the nationwide level was whether Hone Harawira would win Te Tai Tokerau, and that wasn’t going to affect who was in government.  By 10pm it was pretty clear Harawira was out (though he hadn’t conceded) and that Internet Mana had been, in his opponent’s memorable phrase, “all steam and no hangi.”

Jonathan Marshall (@jmarshallnz) has posted swings in each electorate, for the party vote and electorate vote. He also has an interactive Sainte-Laguë seat allocation calculator and has published the data (complete apart from special votes) in a convenient form for y’all to play with.

David Heffernan (@kiwipollguy) collected a bunch of poll, poll average, and pundit predictions, and writes about them here. The basic summary is that they weren’t very good, though there weren’t any totally loony ones, as there were for the last US Presidential election. Our pundits seem to be moderately well calibrated to reality, but there’s a lot of uncertainty in the system and the improvement from averaging seems pretty small.  The only systematic bias is that the Greens did a bit worse than expected.

Based on his criterion, which is squared prediction error scaled basically by party vote, two single polls — 3 News/Reid at the high end and Herald Digipoll at the low end — spanned almost the entire range of prediction error.

The variation between predictions isn’t actually much bigger than you’d expect by chance. The prediction errors have the mean you’d expect from a random sample of about 400 people, and apart from two outliers they have the right spread as well. On the graph, the red curve is a chi-squared distribution with 9 degrees of freedom, and the black curve is the distribution of the 23 estimates. The outliers are Wikipedia and the last 3 News/Reid Research poll.

elections-dist

About half the predictions were qualitatively wrong: they had National needing New Zealand First or the Conservatives for a majority. The Conservatives were clearly treated unfairly by the MMP threshold. If someone is going to be, I’m glad it’s them, but a party with more votes than the Māori Party, Internet Mana, ACT, United Future, and Legalise Cannabis put together should have a chance to prove their unsuitability in Parliament.

 

September 18, 2014

Interactive election results map

The Herald has an interactive election-results map, which will show results for each polling place as they come in, together with demographic information about each electorate.  At the moment it’s showing the 2011 election data, and the displays are still being refined — but the Herald has started promoting it, so I figure it’s safe for me to link as well.

Mashblock is also developing an election site. At the moment they have enrolment data by age. Half the people under 35 in Auckland Central seem to be unenrolled,which is a bit scary. Presumably some of them are students enrolled at home, and some haven’t been in NZ long enough to enrol, but still.

Some non-citizens probably don’t know that they are eligible — I almost missed out last time. So, if you know someone who is a permanent resident and has lived in New Zealand for a year, you might just ask if they know about the eligibility rules. Tomorrow is the last day.

August 30, 2014

Funding vs disease burden: two graphics

You have probably seen the graphic from vox.comhyU8ohq

 

There are several things wrong with it. From a graphics point of view it doesn’t make any of the relevant comparisons easy. The diameter of the circle is proportional to the deaths or money, exaggerating the differences. And the donation data are basically wrong — the original story tries to make it clear that these are particular events, not all donations for a disease, but it’s the graph that is quoted.

For example, the graph lists $54 million for heart disease, based on the ‘Jump Rope for Heart’ fundraiser. According to Forbes magazine’s list of top charities, the American Heart Association actually received $511 million in private donations in the year to June 2012, almost ten times as much.  Almost as much again came in grants for heart disease research from the National Institutes of Health.

There’s another graph I’ve seen on Twitter, which shows what could have been done to make the comparisons clearer:

BwNxOzdCIAAyIZS

 

It’s limited, because it only shows government funding, not private charity, but it shows the relationship between funding and the aggregate loss of health and life for a wide range of diseases.

There are a few outliers, and some of them are for interesting reasons. Tuberculosis is not currently a major health problem in the US, but it is in other countries, and there’s a real risk that it could spread to the US.  AIDS is highly funded partly because of successful lobbying, partly because it — like TB — is a foreign-aid issue, and partly because it has been scientifically rewarding and interesting. COPD and lung cancer are going to become much less common in the future, as the victims of the century-long smoking epidemic die off.

Depression and injuries, though?

 

Update: here’s how distorted the areas are: the purple number is about 4.2 times the blue number

four-to-one

August 29, 2014

Getting good information to government

On the positive side: there’s a conference of science advisers and people who know about the field here in Auckland at the moment. There’s a blog, and there will soon be videos of the presentations.

On the negative side: Statistics Canada continues to provide an example of how a world-class official statistics agency can go downhill with budget cuts and government neglect.  The latest story is the report on how the Labour Force Survey (which is how unemployment is estimated) was off by 42000 in July. There’s a shorter writeup in Maclean’s magazine, and their archive of stories on StatsCan is depressing reading.

August 19, 2014

“More maps that won’t change your mind about racism in America”

From floatingsheep.org

sheep

Ultimately, despite the centrality of social media to the protests and our ability to come together and reflect on the social problems at the root of Michael Brown’s shooting, these maps, and the kind of data used to create them, can’t tell us much about the deep-seated issues that have led to the killing of yet another unarmed young black man in our country. And they almost certainly won’t change anyone’s mind about racism in America. They can, instead, help us to better understand how these events have been reflected on social media, and how even purportedly global news stories are always connected to particular places in specific ways.

August 8, 2014

History of NZ Parliament visualisation

One frame of a video showing NZ party representation in Parliament over time,

nzparties

made by Stella Blake-Kelly for TheWireless. Watch (and read) the whole thing.