A Table That Shows The UK Region For All Postcode Districts

Are you analysing a bunch of addresses, and want to quickly group them into UK regions? That’s what I was doing recently, and did not find it trivially easy.

A quick visit to your favourite search engine will reveal a list of UK post code areas, and their corresponding towns. But that’s not actually as useful as it might seem. Many large towns and cities take their postcode from another large town or city, often in a different county. Basingstoke (Hampshire) has RG postcodes (Reading, Berkshire), for example.

In London, the problem is reversed. The capital has eight of its own postcodes, but the outer London boroughs have their own. Sorting a diverse list of postcodes does not immediately reveal which are ‘London’.

Sometimes it’s better to group locations by broader UK regions. That’s what I wanted to do with a list of over a thousand UK addresses. Eventually I found a site that (in the hope of selling you a handy map) groups all the postcodes by region. I was able to create a lookup table from that information, which I could then use to sort and count the number of addresses in each region. Continue reading “A Table That Shows The UK Region For All Postcode Districts”

Statistician Solves Famous Mathematical Conjecture and Nobody Notices

The discovery was like a religious epiphany and a reward in itself

Via Wired, a delightful news story from Quanta Magazine about a retired statistician who solved a famous mathematical conjecture.

Thomas Royen, of Schwalbach am Taunus in Germany, solved the Gaussian Correlation Inequality conjecture (GCI), a problem that had eluded mathematicians since the 1950s. Royen’s breakthrough came by applying statistical methods and functions to a problem that others had been trying to solve using geometry. This has wonderful anecodtal value when we think about problem solving in general: someone with a different point of view was able to crack a conundrum that had eluded the most eminent of tenured mathematicians for two generations. Continue reading “Statistician Solves Famous Mathematical Conjecture and Nobody Notices”

‘1 in 5 Muslims’: How not to do a survey

The Sun have an alarming – some might say incendiary – headline on its front page today:

1 in 5 Brit Muslims’ sympathy for jihadis

CUc8VdfWsAEyOyx.jpg-largeThere are two aspects to the report by political editor Tom Newton-Dunn that suggest the figure is unlikely to be accurate. Continue reading “‘1 in 5 Muslims’: How not to do a survey”

The soundbite stats we need to win the argument on welfare

I enjoyed these tweets from Laurie Penny, tweeting as @BBCExtraGuest during Question Tim tonight.

The tabloids regularly publish their deceptive anecdata, building over time the impression of welfare abuse.

The result is that the public’s understanding of welfare is warped beyond what is democratically healthy:

The British public believe benefit fraud is a big problem. A recent poll by the TUC showed people believe 27% of the welfare budget is fraudulently claimed.

The reality is very different. Last year, 0.7% of total benefit expenditure was overpaid due to fraud, according to the DWP’s official estimates.

I think that simple, tweetable statistics that put the extent of the welfare ‘problem’ into perspective are the essential weapon the Left needs in its quest to protect the welfare state. Every labour activist needs to be prepped to reel off the facts when they knock on doors and make calls. Every left-leaner should have these figures on the tip of their tongue, ready to rebut the casual myths that their friends, family and colleagues might casually drop into the conversation. (Of course the professional politicians can already do this, but it is rare that Liam Byrne MP is available to stand in the petrol station forecourt, personally explaining to those filling up their tanks that the big stacks of Mail and Express over there are peddling propaganda).

What might the statistics be? In addition to the figures above about welfare fraud vs tax evasion, we need to know the figures for JSA and disability benefits as a proportion of the total welfare bill. Comparisons should be made with defence spending and corporate tax breaks.

One might say that the reason that the myths and misinformation persists is that human interest stories work better than figures. But I think that is a received wisdom that may not be quite true. Figures like those above are easy to remember and repeat.

Moreover, it is not a given that the human interest angle will always be persuasive. ‘Benefit Scroungers’ stories work because You The Taxpayer are the victim of the piece. On the other side of the debate, when we hear the horror stories of welfare cuts or denial, someone else is the victim. There is a world of difference between these different types of stories, and it gives those seeking to divide and obfuscate the upper hand. Perhaps succinct figures, soundbite stats, could give us an edge?