David Cameron Case Study - Management Assignment Help

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ABSTRACT 

[David Cameron]'s broadcast committed two serious errors, or what you might call stat crimes. First it muddled 'deficit' (the amount by which spending exceeds income in any year) with 'debt' (the total amount owed by the Government). You might think it is a distinction a Prime Minister should understand. And then it confused a 'fall in the rate of increase' with 'a fall'.  

FULL TEXT 

Confusion, sloppiness and downright lies mean many published stats are not all they seem, finds Alex Benady.  The Conservatives came to power in 2009 promising to fix the economy But by January this year it was far from fixed. In fact it seemed to be floundering. Anxious to remedy that perception, David Cameron appeared in a party political broadcast that set out to prove his policies were working.  

Cameron said he would 'give people the facts'. Then a caption came up saying: 'The deficit has been reduced by 25 per cent.' Towards the end of the broadcast Cameron looked into the camera and concluded: 'So though this Government has had to make some difficult decisions, we are making progress. We are paying down Britain's debts.'  

It sounded persuasive. Even more so when the claim was repeated in news reports the next day. It seemed that the Tories were indeed fixing our finances. The only problem was it wasn't strictly true. Far from being paid down, the national debt was increasing. What's more, although it is true the deficit was down 25 per cent, if you exclude a one-offpounds 28bn contribution from the Royal Mail pension fund, the reduction was closer to five per cent.  Cameron's broadcast committed two serious errors, or what you might call stat crimes. First it muddled 'deficit' (the amount by which spending exceeds income in any year) with 'debt' (the total amount owed by the Government). You might think it is a distinction a Prime Minister should understand. And then it confused a 'fall in the rate of increase' with 'a fall'.  

It may sound like hair splitting. But the broadcast and its subsequent reporting had a serious effect on national debate. It created a state of such confusion about the basic facts of the economy that even well informed people could not engage with the subject. The head of economics at one of the UK's top universities was moved to comment : 'I can't listen to stories about the debt any more because I just don't understand what is being said.'  The truth is that most of us do not give much thought to statistics most of the time, even though they are the way we inform ourselves about almost everything beyond our own direct experience. They are the thin layer of steely fact that runs through the mush of wishful thinking, impression and anecdote to form our view of the world.  And even though they are so powerful, or perhaps because they are so powerful, they remain curiously unaccountable, impervious to logical analysis in a way we would not tolerate with words. 'Too many of us, when we see a number, just let it wash over us because so many of us have a problem with even basic statistics,' says Will Moy, director of Full Fact, an organisation that promotes accuracy in public debate.  'Bad information makes for bad decisions and misunderstanding of how the world works on important issues.' And, it has to be said, on lesser commercial issues that can be presented as significant because they have numbers attached; which town buys the most marital aids

COMMON STATISTICAL MISTAKES  

1. Sometimes errors are very basic indeed, such as the failure to distinguish between millions and billions, says Labour peer Lord Lipsey.  

2. The use of what Will Moy calls 'zombie statistics' - ones that sound plausible but that on closer inspection are PDF GENERATED BY PROQUEST.COM Page 2 of 4five, ten or 20 years old.  

3. Consistently quoting the top figure from a range. Often statistics come as a range of possibilities. To pick the top figure may create a good headline, but it probably doesn't represent the truth.  

4. False inference. A million foreigners may have entered the country and not be in registered employment. It does not mean there are a million foreigners claiming benefits.  

5. Confusing decline and rate of decline. In year one I picked 500 apples. In year two I picked 520, in year three 525. The rate of growth has declined, although the absolute number of apples picked has increased.  6. Ascribing false significance. Just by random variation some samples produce slightly bigger or smaller results than others. If changes are small - under three per cent - there is no way of knowing whether they reflect something different in the real world or are a sampling error.

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