Ian Stewart, Author at żěè¶ĚĘÓƵ Science news and science articles from żěè¶ĚĘÓƵ Sun, 12 Jul 2026 10:52:44 +0000 en-US hourly 1 https://wordpress.org/?v=7.0.1 242057827 Seven equations that rule your world /article/1968133-seven-equations-that-rule-your-world/?utm_campaign=RSS|NSNS&utm_content=currents&utm_medium=RSS&utm_source=NSNS Wed, 08 Feb 2012 18:00:00 +0000 http://mg21328516.600 [video_player id=”lHin0oae”]Video: Equations that rule the world
The Pythagoreans figured out what makes strings sound harmonious
The Pythagoreans figured out what makes strings sound harmonious
(Image: Nils Jorgensen/Rex Features)

THE alarm rings. You glance at the clock. The time is 6.30 am. You haven’t even got out of bed, and already at least six mathematical equations have influenced your life. The memory chip that stores the time in your clock couldn’t have been devised without a key equation in quantum mechanics. Its time was set by a radio signal that we would never have dreamed of inventing were it not for James Clerk Maxwell’s four equations of electromagnetism. And the signal itself travels according to what is known as the wave equation.

We are afloat on a hidden ocean of equations. They are at work in transport, the financial system, health and crime prevention and detection, communications, food, water, heating and lighting. Step into the shower and you benefit from equations used to regulate the water supply. Your breakfast cereal comes from crops that were bred with the help of statistical equations. Drive to work and your car’s aerodynamic design is in part down to the Navier-Stokes equations that describe how air flows over and around it. Switching on its satnav involves quantum physics again, plus Newton’s laws of motion and gravity, which helped launch the geopositioning satellites and set their orbits. It also uses random number generator equations for timing signals, trigonometric equations to compute location, and special and general relativity for precise tracking of the satellites’ motion under the Earth’s gravity.

“We are afloat on a hidden ocean of equations. They are at work in transport, health, communications, food, water, heating and lighting”

Without equations, most of our technology would never have been invented. Of course, important inventions such as fire and the wheel came about without any mathematical knowledge. Yet without equations we would be stuck in a medieval world.

Equations reach far beyond technology too. Without them, we would have no understanding of the physics that governs the tides, waves breaking on the beach, the ever-changing weather, the movements of the planets, the nuclear furnaces of the stars, the spirals of galaxies – the vastness of the universe and our place within it.

There are thousands of important equations. The seven I focus on here – the wave equation, Maxwell’s four equations, the Fourier transform and Schrödinger’s equation – illustrate how empirical observations have led to equations that we use both in science and in everyday life.

Graphic: See the seven equations

First, the wave equation. We live in a world of waves. Our ears detect waves of compression in the air as sound, and our eyes detect light waves. When an earthquake hits a town, the destruction is caused by seismic waves moving through the Earth.

Mathematicians and scientists could hardly fail to think about waves, but their starting point came from the arts: how does a violin string create sound? The question goes back to the ancient Greek cult of the Pythagoreans, who found that if two strings of the same type and tension have lengths in a simple ratio, such as 2:1 or 3:2, they produce notes that, together, sound unusually harmonious. More complex ratios are discordant and unpleasant to the ear. It was Swiss mathematician Johann Bernoulli who began to make sense of these observations. In 1727 he modelled a violin string as a large number of closely spaced point masses, linked together by springs. He used Newton’s laws to write down the system’s equations of motion, and solved them. From the solutions, he concluded that the simplest shape for a vibrating string is a sine curve. There are other modes of vibration as well – sine curves in which more than one wave fits into the length of the string, known to musicians as harmonics.

From waves to wireless

Almost 20 years later, Jean Le Rond d’Alembert followed a similar procedure, but he focused on simplifying the equations of motion rather than their solutions. What emerged was an elegant equation describing how the shape of the string changes over time. This is the wave equation, and it states that the acceleration of any small segment of the string is proportional to the tension acting on it. It implies that waves whose frequencies are not in simple ratios produce an unpleasant buzzing noise known as “beats”. This is one reason why simple numerical ratios give notes that sound harmonious.

The wave equation can be modified to deal with more complex, messy phenomena, such as earthquakes. Sophisticated versions of the wave equation let seismologists detect what is happening hundreds of miles beneath our feet. They can map the Earth’s tectonic plates as one slides beneath another, causing earthquakes and volcanoes. The biggest prize in this area would be a reliable way to predict earthquakes and volcanic eruptions, and many of the methods being explored are underpinned by the wave equation.

But the most influential insight from the wave equation emerged from the study of Maxwell’s equations of electromagnetism. In 1820, most people lit their houses using candles and lanterns. If you wanted to send a message, you wrote a letter and put it on a horse-drawn carriage; for urgent messages, you omitted the carriage. Within 100 years, homes and streets had electric lighting, telegraphy meant messages could be transmitted across continents, and people even began to talk to each other by telephone. Radio communication had been demonstrated in laboratories, and one entrepreneur had set up a factory selling “wirelesses” to the public.

This social and technological revolution was triggered by the discoveries of two scientists. In about 1830, established the basic physics of electromagnetism. Thirty years later, embarked on a quest to formulate a mathematical basis for Faraday’s experiments and theories.

At the time, most physicists working on electricity and magnetism were looking for analogies with gravity, which they viewed as a force acting between bodies at a distance. Faraday had a different idea: to explain the series of experiments he conducted on electricity and magnetism, he postulated that both phenomena are fields which pervade space, change over time and can be detected by the forces they produce. Faraday posed his theories in terms of geometric structures, such as lines of magnetic force.

Maxwell reformulated these ideas by analogy with the mathematics of fluid flow. He reasoned that lines of force were analogous to the paths followed by the molecules of a fluid and that the strength of the electric or magnetic field was analogous to the velocity of the fluid. By 1864 Maxwell had written down four equations for the basic interactions between the electrical and magnetic fields. Two tell us that electricity and magnetism cannot leak away. The other two tell us that when a region of electric field spins in a small circle, it creates a magnetic field, and a spinning region of magnetic field creates an electric field.

But it was what Maxwell did next that is so astonishing. By performing a few simple manipulations on his equations, he succeeded in deriving the wave equation and deduced that light must be an electromagnetic wave. This alone was stupendous news, as no one had imagined such a fundamental link between light, electricity and magnetism. And there was more. Light comes in different colours, corresponding to different wavelengths. The wavelengths we see are restricted by the chemistry of the eye’s light-detecting pigments. Maxwell’s equations led to a dramatic prediction – that electromagnetic waves of all wavelengths should exist. Some, with much longer wavelengths than we can see, would transform the world: radio waves.

“Maxwell’s equations led to the dramatic prediction that electromagnetic waves of all wavelengths should exist. Radio waves went on to transform the world”

In 1887, Heinrich Hertz demonstrated radio waves experimentally, but he failed to appreciate their most revolutionary application. If you could impress a signal on such a wave, you could talk to the world. Nikola Tesla, Guglielmo Marconi and others turned the dream into reality, and the whole panoply of modern communications, from radio and television to radar and microwave links for cellphones, followed naturally. And it all stemmed from four equations and a couple of short calculations. Maxwell’s equations didn’t just change the world. They opened up a new one.

Just as important as what Maxwell’s equations do describe is what they don’t. Although the equations revealed that light was a wave, physicists soon found that its behaviour was sometimes at odds with this view. Shine light on a metal and it creates electricity, a phenomenon called the photoelectric effect. It made sense only if light behaved like a particle. So was light a wave or a particle? Actually, a bit of both. Matter was made from quantum waves, and a tightly knit bunch of waves acted like a particle.

Dead or alive

In 1927 Erwin Schrödinger wrote down an equation for quantum waves. It fitted experiments beautifully while painting a picture of a very strange world, in which fundamental particles like the electron are not well-defined objects, but probability clouds. An electron’s spin is like a coin that can be half heads and half tails until it hits a table. Soon theorists were worrying about all manner of quantum weirdness, such as cats that are simultaneously dead and alive, and parallel universes in which Adolf Hitler won the second world war.

Quantum mechanics isn’t confined to such philosophical enigmas. Almost all modern gadgets – computers, cellphones, games consoles, cars, refrigerators, ovens – contain memory chips based on the transistor, whose operation relies on the quantum mechanics of semiconductors. New uses for quantum mechanics arrive almost weekly. Quantum dots – tiny lumps of a semiconductor – can emit light of any colour and are used for biological imaging, where they replace traditional, often toxic, dyes. Engineers and physicists are trying to invent a quantum computer, one which can perform many different calculations in parallel, just like the cat that is both alive and dead.

Lasers are another application of quantum mechanics. We use them to read information from tiny pits or marks on CDs, DVDs and Blu-ray discs. Astronomers use lasers to measure the distance from the Earth to the moon. It might even be possible to launch space vehicles from Earth on the back of a powerful laser beam.

The final chapter in this story comes from an equation that helps us make sense of waves. It starts in 1807, when Joseph Fourier devised an equation for heat flow. He submitted a paper on it to the French Academy of Sciences, but it was rejected. In 1812, the academy made heat the topic of its annual prize. Fourier submitted a longer, revised paper – and won.

The most intriguing aspect of Fourier’s prize-winning paper was not the equation, but how he solved it. A typical problem was to find how the temperature along a thin rod changes as time passes, given the initial temperature profile. Fourier could solve this equation with ease if the temperature varied like a sine wave along its length. So he represented a more complicated profile as a combination of sine curves with different wavelengths, solved the equation for each component sine curve, and added these solutions together. Fourier claimed that this method worked for any profile whatsoever, even a one where the temperature suddenly jumps in value. All you had to do was add up an infinite number of contributions from sine curves with more and more wiggles.

Even so, Fourier’s new paper was criticised for not being rigorous enough, and once more the French academy refused to publish it. In 1822 Fourier ignored the objections and published his theory as a book. Two years later, he got himself appointed secretary of the academy, thumbed his nose at his critics, and published his original paper in the academy’s journal. However, the critics did have a point. Mathematicians were starting to realise that infinite series were dangerous beasts; they didn’t always behave like nice, finite sums. Resolving these issues turned out to be distinctly difficult, but the final verdict was that Fourier’s idea could be made rigorous by excluding highly irregular profiles. The result is the Fourier transform, an equation that treats a time-varying signal as the sum of a series of component sine curves and calculates their amplitudes and frequencies.

Today the Fourier transform affects our lives in myriad ways. For example, we can use it to analyse the vibrational signal produced by an earthquake and to calculate the frequencies at which the energy imparted by the shaking ground is greatest. A sensible step towards earthquake-proofing a building is to make sure that the building’s preferred frequencies are different from the earthquake’s.

“Today the Fourier transform affects our lives in myriad ways, from finding structures in DNA to compressing digital photographs”

Other applications include removing noise from old sound recordings, finding the structure of DNA using X-ray images, improving radio reception and preventing unwanted vibrations in cars. Plus there is one that most of us unwittingly take advantage of every time we take a digital photograph.

If you work out how much information is required to represent the colour and brightness of each pixel in a digital image, you will discover that a digital camera seems to cram into its memory card about 10 times as much data as the card can possibly hold. Cameras do this using JPEG data compression, which combines five different compression steps. One of them is a digital version of the Fourier transform, which works with a signal that changes not over time but across the image. The mathematics is virtually identical. The other four steps reduce the data even further, to about one-tenth of the original amount.

These are just seven of the many equations that we encounter every day, not realising they are there. But the impact of equations on history goes much further. A truly revolutionary equation can have a greater impact on human existence than all the kings and queens whose machinations fill our history books.

There is (or may be) one equation, above all, that physicists and cosmologists would dearly love to lay their hands on: a theory of everything that unifies quantum mechanics and relativity. The best known of the many candidates is the theory of superstrings. But for all we know, our equations for the physical world may just be oversimplified models that fail to capture the deep structure of reality. Even if nature obeys universal laws, they might not be expressible as equations.

Some scientists think that it is time we abandoned traditional equations altogether in favour of algorithms – more general recipes for calculating things that involve decision-making. But until that day dawns, if ever, our greatest insights into nature’s laws will continue to take the form of equations, and we should learn to understand them and appreciate them. Equations have a track record. They really have changed the world and they will change it again.

Seven equations that rule your world

The origin of equations

The ancient Babylonians and Greeks knew about equations, though they wrote them using words and pictures. For the past 500 years, mathematicians and scientists have used symbols, the crucial one being the equals sign. Unusually, we know who invented it, and why. It was Robert Recorde, who in 1557 wrote in his treatise The Whetstone of Witte: “To avoide the tediouse repetition of these woordes: is equalle to: I will sette as I doe often in woorke use, a paire of paralleles, or gemowe lines of one lengthe: bicause noe .2. thynges, can be moare equalle.”

Theorems and theories

Some equations present logical relations between mathematical quantities, and the task of mathematicians is to prove they are valid. Others provide information about an unknown quantity; here the task is to solve the equation and make the unknown known. Equations in pure mathematics are generally of the first kind: they reveal patterns and regularities in mathematics itself. Pythagoras’s theorem, an equation expressed in the language of geometry, is an example. Given Euclid’s basic geometric assumptions, Pythagoras’s theorem is true.

Equations in applied mathematics and mathematical physics are usually of the second kind. They express properties of the universe that could, in principle, have been otherwise. For example, Newton’s law of gravity tells us how to calculate the attractive force between two bodies. Solving the resulting equations tells us how planets orbit the sun or how to plot a trajectory for a space probe. But Newton’s law isn’t a mathematical theorem; the law of gravity might have been different. Indeed, it is different: Einstein’s general relativity improves on Newton. And even that theory may not be the last word.

Our choice of Maxwell’s equations

In this story, and in his latest book, 17 Equations that Changed the World, Ian Stewart uses Maxwell’s equation for electromagnetic waves propagating in a vacuum. In the accompanying video, we use the longer version of the equation that doesn’t depend on the waves moving through a vacuum.

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Nothingness: Mathematics starts with an empty set /article/1965675-nothingness-mathematics-starts-with-an-empty-set/?utm_campaign=RSS|NSNS&utm_content=currents&utm_medium=RSS&utm_source=NSNS Wed, 16 Nov 2011 18:00:00 +0000 http://mg21228390.600 1965675 Electoral dysfunction: Why democracy is always unfair /article/1948039-electoral-dysfunction-why-democracy-is-always-unfair/?utm_campaign=RSS|NSNS&utm_content=currents&utm_medium=RSS&utm_source=NSNS Wed, 28 Apr 2010 17:00:00 +0000 http://mg20627581.400 IN AN ideal world, elections should be two things: free and fair. Every adult, with a few sensible exceptions, should be able to vote for a candidate of their choice, and each single vote should be worth the same. Ensuring a free vote is a matter for the law. Making elections fair is more a matter for mathematicians. They have been studying voting systems for hundreds of years, looking for sources of bias that distort the value of individual votes, and ways to avoid them. Along the way, they have turned up many paradoxes and surprises. What they have not done is come up with the answer. With good reason: it probably doesn’t exist. The many democratic electoral systems in use around the world attempt to strike a balance between mathematical fairness and political considerations such as accountability and the need for strong, stable government. Take first-past-the-post or “plurality” voting, which used for national elections in the US, Canada, India – and the UK, which goes to the polls next week. Its principle is simple: each electoral division elects one representative, the candidate who gained the most votes. This system scores well on stability and accountability, but in terms of mathematical fairness it is a dud. Votes for anyone other than the winning candidate are disregarded. If more than two parties with substantial support contest a constituency, as is typical in Canada, India and the UK, a candidate does not have to get anything like 50 per cent of the votes to win, so a majority of votes are “lost”. Dividing a nation or city into bite-sized chunks for an election is itself a fraught business (see “Borderline case”, below) that invites other distortions, too. A party can win outright by being only marginally ahead of its competitors in most electoral divisions. In the UK general election in 2005, the ruling Labour party won 55 per cent of the seats on just 35 per cent of the total votes. If a candidate or party is slightly ahead in a bare majority of electoral divisions but a long way behind in others, they can win even if a competitor gets more votes overall – as happened most notoriously in recent history in the US presidential election of 2000, when George W. Bush narrowly defeated Al Gore.

Borderline case

In first-past-the-post or “plurality” systems, borders matter. To ensure that each vote has roughly the same weight, each constituency should have roughly the same number of voters. Threading boundaries between and through centres of population on the pretext of ensuring fairness is also a great way to cheat for your own benefit – a practice known as , after a 19th-century governor of Massachusetts, Elbridge Gerry, who created an electoral division reminded a local newspaper editor of a salamander. Suppose a city controlled by the Liberal Republican (LR) party has a voting population of 900,000 divided into three constituencies. Polls show that at the next election LR is heading for defeat – 400,000 people intend to vote for it but the 500,000 others will opt for the Democratic Conservative (DC) party. If the boundaries were to keep the proportions the same, each constituency would contain roughly 130,000 LR voters and 170,000 DC voters, and DC would take all three seats – the usual inequity of a plurality voting system. In reality, voters inclined to vote for one party or the other will probably clump together in the same neighbourhoods of the city, so LR might well retain one seat. However, it could be all too easy for LR to redraw the boundaries to reverse the result and secure itself a majority – as these two dividing strategies show.
Electoral dysfunction: Why democracy is always unfair The anomalies of a plurality voting system can be more subtle, though, as mathematician at the University of California, Irvine, showed. Suppose 15 people are asked to rank their liking for milk (M), beer (B), or wine (W). Six rank them M-W-B, five B-W-M, and four W-B-M. In a plurality system where only first preferences count, the outcome is simple: milk wins with 40 per cent of the vote, followed by beer, with wine trailing in last. So do voters actually prefer milk? Not a bit of it. Nine voters prefer beer to milk, and nine prefer wine to milk – clear majorities in both cases. Meanwhile, 10 people prefer wine to beer. By pairing off all these preferences, we see the truly preferred order to be W-B-M – the exact reverse of what the voting system produced. In fact Saari showed that given a set of voter preferences you can design a system that produces any result you desire. In the example above, simple plurality voting produced an anomalous outcome because the alcohol drinkers stuck together: wine and beer drinkers both nominated the other as their second preference and gave milk a big thumbs-down. Similar things happen in politics when two parties appeal to the same kind of voters, splitting their votes between them and allowing a third party unpopular with the majority to win the election. Can we avoid that kind of unfairness while keeping the advantages of a first-past-the-post system? Only to an extent. One possibility is a second “run-off” election between the two top-ranked candidates, as happens in France and in many presidential elections elsewhere. But there is no guarantee that the two candidates with the widest potential support even make the run-off. In the 2002 French presidential election, for example, so many left-wing candidates stood in the first round that all of them were eliminated, .

Order, order

Another strategy allows voters to place candidates in order of preference, with a 1, 2, 3 and so on. After the first-preference votes have been counted, the candidate with the lowest score is eliminated and the votes reapportioned to the next-choice candidates on those ballot papers. This process goes on until one candidate has the support of over 50 per cent of the voters. This system, called the instant run-off or alternative or preferential vote, is used in elections to the Australian House of Representatives, as well as in several US cities. It . Preferential voting comes closer to being fair than plurality voting, but it does not eliminate ordering paradoxes. The , a French mathematician, noted this as early as 1785. Suppose we have three candidates, A, B and C, and three voters who rank them A-B-C, B-C-A and C-A-B. Voters prefer A to B by 2 to 1. But B is preferred to C and C preferred to A by the same margin of 2 to 1. To quote the : “Everybody has won and all must have prizes.” One type of voting system avoids such circular paradoxes entirely: proportional representation. Here a party is awarded a number of parliamentary seats in direct proportion to the number of people who voted for it. Such a system is undoubtedly fairer in a mathematical sense than either plurality or preferential voting, but it has political drawbacks. It implies large, multi-representative constituencies; the best shot at truly proportional representation comes with just one constituency, the system used in Israel. But large constituencies weaken the link between voters and their representatives. Candidates are often chosen from a centrally determined list, so voters have little or no control over who represents them. What’s more, proportional systems tend to produce coalitions of two or more parties, potentially leading to unstable and ineffectual government – although plurality systems are not immune to such problems, either (see “Power in the balance”). Editorial: Giving democracy a shot in the arm Proportional representation has its own mathematical wrinkles. There is no way, for example, to allocate a whole number of seats in exact proportion to a larger population. This can lead to an odd situation in which increasing the total number of seats available reduces the representation of an individual constituency, even if its population stays the same (see “Proportional paradox”). Such imperfections led the American economist Kenneth Arrow to list in 1963 the general attributes of an idealised fair voting system. He suggested that voters should be able to express a complete set of their preferences; no single voter should be allowed to dictate the outcome of the election; if every voter prefers one candidate to another, the final ranking should reflect that; and if a voter prefers one candidate to a second, introducing a third candidate should not reverse that preference. All very sensible. There’s just one problem: Arrow and others went on to prove that . In particular, there will always be the possibility that one voter, simply by changing their vote, can change the overall preference of the whole electorate. So we are left to make the best of a bad job. Some less fair systems produce governments with enough power to actually do things, though most voters may disapprove; some fairer systems spread power so thinly that any attempt at government descends into partisan infighting. Crunching the numbers can help, but deciding which is the lesser of the two evils is ultimately a matter not for mathematics, but for human judgement.

Proportional paradox

Although elections to the US House of Representatives use a first-past-the-post voting system, the constitution requires that seats be – that is, divvied up proportionally. In 1880, the chief clerk of the US Census Bureau, Charles Seaton, discovered that Alabama would get eight seats in a 299-seat House, but only seven in a 300-seat House. This “Alabama paradox” was caused by an algorithm known as the largest remainder method, which was used to round the number of seats a state would receive under strict proportionality to a whole number. Suppose for simplicity’s sake that a nation of 39 million voters has a parliament with four seats – giving a quota of 9.75 million voters per seat. The seats must, however, be shared among three states, Alabaska, Bolorado and Carofornia, with voting populations of 21, 13 and 5 million, respectively. Dividing these numbers by the quota gives each state’s fair proportion of seats. Rounded down to an integer, this number of seats is given to the states. Any seats left over go to the state or states with the highest remainders. See the results The rounded-down integers allocate three seats. The fourth goes to Carofornia, the state with the largest remainder. Suppose now the number of seats increases from four to five. The quota is 39 million divided by 5, or 7.8 million, and so our table becomes this: The rounded-down integers account for three seats as before. The two spare go to Alabaska and Bolorado, which have the two largest remainders, and Carofornia loses its only seat. (The US Constitution stipulates that each state must have at least one representative, which would protect Carofornia in this case – the size of the House would have to be increased by one seat.) The precise conditions that lead to the Alabama paradox are mathematically complex. For three states they can be portrayed graphically, as in this diagram. The left-hand diagram shows the populations (as a fraction of the country’s total) and fair proportions of three states in the case of four seats; the right-hand side superimposes the diagram for five seats. The Alabama paradox occurs for the shaded population combinations: our example lies in the leftmost orange-shaded region. Such quirks mean that seats in proportional systems are now generally apportioned using algorithms known as . These work by dividing voting populations by a common factor so that when the fair proportions are rounded to a whole number they add up to the number of available seats. But this method is not foolproof: it sometimes gives a constituency more seats than the whole number closest to its fair proportion.
Electoral dysfunction: Why democracy is always unfair Electoral dysfunction: Why democracy is always unfairElectoral dysfunction: Why democracy is always unfair

Power in the balance

One criticism of proportional voting systems is that they make it less likely that one party wins a majority of the seats available, thus increasing the power of smaller parties as “king-makers” who can swing the balance between rival parties as they see fit. The same can happen in a plurality system if the electoral arithmetic delivers a hung parliament, in which no party has an overall majority – as might happen in the UK after its election next week. Where does the power reside in such situations? One way to quantify that question is the . First, list all combinations of parties that could form a majority coalition, and in all of those coalitions count how many times a party is a “swing” partner that could destroy the majority if it dropped out. Dividing this number by the total number of swing partners in all possible majority coalitions gives a party’s power index. For example, imagine a parliament of six seats in which party A has three seats, party B has two and party C has one. There are three ways to make a coalition with a majority of at least four votes: AB, AC and ABC. In the first two instances, both partners are swing partners. In the third instance, only A is – if either B or C dropped out, the remaining coalition would still have a majority. Among the total of five swing partners in the three coalitions, A crops up three times and B and C once each. So A has a power index of 3 ÷ 5, or 0.6, or 60 per cent – more than the 50 per cent of the seats it holds – and B and C are each “worth” just 20 per cent. In a realistic situation, the calculations are more involved. This diagram shows how the power shifts dramatically when there is no majority in a in which five voting blocs are represented.
Electoral dysfunction: Why democracy is always unfair

The UK’s next prime minister

Psychologists Rob Jenkins and Tony McCarthy from the University of Glasgow, and Richard Wiseman of the University of Hertfordshire, have run a subliminal online experiment with żěè¶ĚĘÓƵ to predict the outcome of the UK general election next week. And the result is:

Conservatives 290

Labour 247

Liberal Democrats 70

Were they right? They explain their method – and its success or failure – in the 15 May issue of żěè¶ĚĘÓƵ.
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The scientific guide to gift wrapping /article/1929030-the-scientific-guide-to-gift-wrapping/?utm_campaign=RSS|NSNS&utm_content=currents&utm_medium=RSS&utm_source=NSNS Wed, 17 Dec 2008 18:00:00 +0000 http://mg20026873.800 1929030 Solving postal problem could win million-dollar prize /article/1894804-solving-postal-problem-could-win-million-dollar-prize/?utm_campaign=RSS|NSNS&utm_content=currents&utm_medium=RSS&utm_source=NSNS Wed, 18 Jun 2008 17:00:00 +0000 http://mg19826611.500 1894804 Cracking the power-line communication conundrum /article/1887050-cracking-the-power-line-communication-conundrum/?utm_campaign=RSS|NSNS&utm_content=currents&utm_medium=RSS&utm_source=NSNS Wed, 21 Mar 2007 18:00:00 +0000 http://mg19325961.700 1887050 Ride the celestial subway /article/1880681-ride-the-celestial-subway/?utm_campaign=RSS|NSNS&utm_content=currents&utm_medium=RSS&utm_source=NSNS Wed, 22 Mar 2006 19:00:00 +0000 http://mg18925441.300 1880681 The prime number hunters close in /article/1877970-the-prime-number-hunters-close-in/?utm_campaign=RSS|NSNS&utm_content=currents&utm_medium=RSS&utm_source=NSNS Wed, 03 Aug 2005 18:00:00 +0000 http://mg18725112.000 1877970 In the lap of the gods /article/1874351-in-the-lap-of-the-gods/?utm_campaign=RSS|NSNS&utm_content=currents&utm_medium=RSS&utm_source=NSNS Fri, 24 Sep 2004 23:00:00 +0000 http://mg18324665.300 1874351 How the species became /article/1871839-how-the-species-became/?utm_campaign=RSS|NSNS&utm_content=currents&utm_medium=RSS&utm_source=NSNS Fri, 10 Oct 2003 23:00:00 +0000 http://mg18024165.500 1871839