In , the French Ministry of Justice ordered the creation of a national collection of crime records. It seems to have been the first of its kind anywhere in the world—the statistics of every arrest and conviction in the country, broken down by region, assembled and ready for analysis. This was an early instance of Big Data—the first time that mathematical analysis had been applied in earnest to the messy and unpredictable realm of human behavior.
Or maybe not so unpredictable. In the early eighteen-thirties, a Belgian astronomer and mathematician named Adolphe Quetelet analyzed the numbers and discovered a remarkable pattern. The crime records were startlingly consistent. Year after year, irrespective of the actions of courts and prisons, the number of murders, rapes, and robberies reached almost exactly the same total.
How many will be forgers, how many poisoners. To Quetelet, the evidence suggested that there was something deeper to discover. We can now forecast, with remarkable accuracy, the number of women in Germany who will choose to have a baby each year, the number of car accidents in Canada, the number of plane crashes across the Southern Hemisphere, even the number of people who will visit a New York City emergency room on a Friday evening. In some ways, this is what you would expect from any large, disordered system. Think about the predictable and quantifiable way that gases behave. It might be impossible to trace the movement of each individual gas molecule, but the uncertainty and disorder at the molecular level wash out when you look at the bigger picture.
Similarly, larger regularities emerge from our individually unpredictable lives. The trouble comes when you try to go the other way—to learn something about us as individuals from how we behave as a collective. And, of course, those answers are often the ones we most want. He agreed to pay a ninety-year-old woman twenty-five hundred francs every month until her death, whereupon he would take possession of her apartment in Arles. At the time, the average life expectancy of French women was She survived for thirty-two years after their deal was signed, outliving Raffray, who died at seventy-seven.
By then, he had paid more than twice the market value for an apartment he would never live in. Raffray learned the hard way that people are not well represented by the average. Every day, millions of people, David Spiegelhalter included, swallow a small white statin pill to reduce the risk of heart attack and stroke. If you are one of those people, and go on to live a long and happy life without ever suffering a heart attack, you have no way of knowing whether your daily statin was responsible or whether you were never going to have a heart attack in the first place.
Of a thousand people who take statins for five years, the drugs will help only eighteen to avoid a major heart attack or stroke. The fact that they produce a collective benefit makes them worth taking. Despite the grand promises of Big Data, uncertainty remains so abundant that specific human lives remain boundlessly unpredictable. Perhaps the most successful prediction engine of the Big Data era, at least in financial terms, is the Amazon recommendation algorithm.
Dombey says, already imagining the business career that young Paul will enjoy. Statisticians have navigated a route to maximum certainty in an uncertain world. In the process, a powerful idea has arisen to form the basis of modern scientific research. A stranger hands you a coin.
You toss the coin twice, and get two heads in a row. Nothing to get excited about just yet. A perfectly fair coin will throw two heads in a row twenty-five per cent of the time—a probability known as the p-value. You keep tossing and get another head.
Then another. Things are starting to look fishy, but even if you threw the coin a thousand times, or a million, you could never be absolutely sure it was rigged. The chances might be minuscule, but in theory a fair coin could still produce any combination of heads. Scientists have picked a path through all this uncertainty by setting an arbitrary threshold, and agreeing that anything beyond that point gives you grounds for suspicion. Since , when the British statistician Ronald Fisher first suggested the convention, that threshold has typically been set at five per cent.
In this case, five heads in a row, with a p-value of 3. This is the underlying principle behind how modern science comes to its conclusions. If the results are too unusual to have happened by chance—at least, not more than one time out of twenty—you have reason to think that your hypothesis has been vindicated. Take a clinical trial on aspirin run by the Oxford medical epidemiologist Richard Peto in Aspirin interferes with the formation of blood clots, and can be used to prevent them in the arteries of the heart or the brain.
Their trial involved 17, people and showed a remarkable effect. In the group that was given a placebo, 1, patients died; of those who had taken the aspirin, only died. The numbers passed the threshold; the team concluded that the aspirin was working. Such statistical methods have become the currency of modern research.
But, unless you are extraordinarily careful, trying to erase uncertainty comes with downsides. The referee wanted to know how many women had been saved by the aspirin, how many men, how many with diabetes, how many in this or that age bracket, and so on. Peto objected. By subdividing the big picture, he argued, you introduce all kinds of uncertainty into the results. For one thing, the smaller the size of the groups considered, the greater the chance of a fluke. The journal was insistent, so Peto relented.
- Between Logic and Intuition: Essays in Honor of Charles Parsons.
- Header 2;
- Advances in Imaging and Electron Physics: 130?
- Using and Handling Data.
- What Baseball Teaches Us About Measuring Talent.
- Contact Us!
He resubmitted the paper with all the subgroups the referee had asked for, but with a sly addition. He also subdivided the results by astrological sign. The easiest way to understand the issue is by returning to the conundrum of the biased coin. List of Research activities New research Discussion papers Events. Statistics Norway — official statistics about Norwegian society since Key figures 5 Population Number of persons registered as living in Norway as per 1 October Go to Population and population changes. The total value of goods and services produced in Norway, divided by the number of inhabitants Go to Annual national accounts.
The share of the labour force that is unemployed sesonally adjusted, May Go to Labour force survey. The rise in prices for a selection of common goods and services over the last twelve months December - December Go to Consumer Price Index.
Net migration: The difference between in-migration and out-migration Go to Immigration and emigration. Search for statistics Search for statistics Search for statistics.
Advanced WooCommerce Reporting – Statistics & Forecast
Adjust the rent? Calculate price changes with CPI. Name statistics Do you wonder how many people have the same name as you? Search by name. Calendar See the advance release calendar Calendar. Subscribe to news Get the latest statistics releases and publications by e-mail Receive e-mail alerts. News Revision of government finance statistics 20 September Revised data on general government revenue and expenditure is now available. CPI up 1. Price increase on natural gas 10 September A reduction in the price of crude oil of almost 5 per cent decreased the producer price index PPI slightly from July to August, but with a sharp increase in the price of natural gas, the drop in the total index was minimal.
Economic trends for Norway and abroad Interest rate likely to have peaked 5 September The Norwegian economy is facing a change of pace.
Copyright 2019 - All Right Reserved