how government manipulate the outcomes of investigations There are lies, damn lies and statistics.

how government manipulate the outcomes of investigations There are lies, damn lies and statistics.

http://www.wrhip.co.uk/statistics.html

Statistics are generally used to bolster a weak argument, as you can basically make them say whatever you want.
By their very nature they can be misleading and with a bit of manipulation, can appear even better.
And of course, that's why politicians use them.
They're also used to try and justify a position.
Typically, it will be stating that say 60% of people and thereby a majority, agree with you.
That may seem fair enough.
Except the fact you realize just because 100% of people would probably agree with free beer and money, it doesn't make it right.
The deceitful way figures are compiled is even more insidious; this aspect of statistics are largely unrecognized and/or forgot.
Subsequently, it goes unchallenged and yet this phenomena corrupts the starting point and the very basis of the definition of the data itself.
Let's explore the way statistics are compiled and used first.
By looking at the make-up of statistics and how they can be both falsely represented and manipulated, to corrupt or distort the true nature of any given situation or argument.
The fixing of the figures starts with the way in which they are compiled.
Now, I don't know if you've noticed, but recently a lot more things appear to be being completed on time and to budget.
One could be forgiven for thinking that workers are getting more efficient, companies are more professional, more determined, that lessons have been learnt from past failed or late projects and work is to a higher standard now.
But you'd be wrong.
In actual fact, there is a slight of hand at play here.
For example, a company is to construct a bridge which with the best professional advice is going to take 4 months to build.
The government and companies alike love putting up signs telling us about their glorious project and when it will be completed by.
But they've cottoned on to something.
In order to avoid a public relations humiliation by overrunning on the project and not opening on time, they don't put a sign up stating the expected opening date is, as fully expected, in 4 months' time.
What they do is to add on a lot more time than is actually needed to finish the project.
So, their sign for the completion date goes up as 6 months.
When they subsequently complete (as expected) in 4 months, they can (rightly) claim they have finished early and bask in the associated glory that they will get for this apparent success.
The railways learnt this lesson years ago.
The problem was so many late trains.
Most people believe that trains are more punctual now, as the statistics show.
But they're wrong.
They simply moved the goal posts.
Any train route that was routinely delayed, simply had the timetable revised; upwards.
So for example, a previously scheduled 3 hour journey would now perhaps be shown as 3 hours 10 minutes which would accommodate the late arrivals; thus creating the illusion that all services were on time.
The other problem which is ruthlessly exploited with figures, is that they can be made to say whatever you want.
Let's say a child scored 10 correct questions out of 100 in a test of a class of 20 children.
And let's say everyone else in the class was a bit dim and only scored 9 or less.
That would mean with a score of just 10/100, the child would come top of the class, first out of 20 children.
Subsequently, you could use the figures to say that the child is really clever, as they had the highest score in the test and came top of the class.
Sounds great.
Until you think about it....whereas in reality, 10 out of 100 is abysmal.
Conversely, if someone were to score 90% in an exam which everyone else who entered got 91% or more, they would come bottom of the class with the worst result.
Consequently, you could use the figures to portray how they came last, worst in class which although true, would thus give the (false) impression they had performed badly.
Of course in actual fact 90% in an exam is very good indeed and would certainly guarantee an A grade, at any level.
The government keep telling us that average wages are going up which frankly, as we all know, is meaningless.
What it actually means is that a few people in London have had a one million pounds bonus and everyone else has had nothing.
But that massive increase for a tiny few drags the average up and looks good to announce.
This misrepresentation can be applied across all subjects and areas of public interest and debate.
And indeed it is, with great vigour and enthusiasm.
The police routinely do it to disguise and distort crime figures, but as we have given enough examples and already touched on the subject (see blog 'Peter Hitchens on Question Time' 6/11/15) we won't go any further at the moment.
Suffice to say they redefine the definition a 'crime' in order to lower the figures.
Think... just because a complaint may be withdrawn does not mean the crime did not take place, but it sure won't be counted.
The official unemployment figures are another fine example.
Nobody believes unemployment is actually falling and they're probably right, it's not.
Again, they start with the definition of being 'unemployed'.
By the simple act of only classing anyone who is claiming job seekers allowance, as 'unemployed', plenty of scope is provided to hive people off on to training schemes, education or indeed other benefits.
Subsequently, these people are simply not counted towards the unemployment figures.
Yet the fact remains they still don't have a job, they're just not claiming JSA; they are still truly unemployed.
Even people who work through an employment agency on temporary assignments with no contracted hours, who technically do not have a job, are not counted.
But it doesn't matter.
Through the distortion of the very definition of unemployment, as being in receipt of JSA, in a single stroke the government can (rightly) state the figures are correct.
Moreover, the more they persuade or indeed force people on to other schemes, the more they can claim that unemployment is falling.
The use of statistics, or more to the point manipulated and therefore corrupt statistics, also forge the basis for what has become a fashionable argument for the government which is based on a false premise.
That argument is for 'evidence based policy'.
This is actually simply a tactic to disguise other failings or concerns, such as financial interest.
Let's explore this ruse a bit further.
Take the Ash die back disease that affected Europe a few years ago, for example.
When this was first detected, warnings and advice were given to the government, as to how best combat possible its spread to Britain.
Common sense would dictate perhaps a ban or testing regime on imports of Ash from the continent; any infected tree would carry the spores of the disease, obviously.
A bit like when there is an outbreak of foot and mouth or some other communicable disease; obviously you restrict free movement.
Amongst other concerns, this advice was indeed given by concerned scientists and alike.
But the government said there was no scientific evidence to prove that banning imports would help stop the spread and that there had to be 'evidence led policy'.
Subsequently, it did indeed come to Britain.
No one knows if it came on the wind or through the import of infected trees, but what would have been so wrong about acting on common sense and banning imports of the affected species?
I mean, it's not rocket science, has never been thought of or done before.
Think France and when they banned the import of British beef due to the outbreak of BSE disease.
To ban the import of an infected product?
Eminently sensible I would have thought.
If there was an outbreak of meningitis at the school your child went to, would you really send them to school, simply because there was no scientific proof your child would definitely catch it?
I don't think so.
There's no scientific evidence that says if a young girl were to go out on her own late at night she would be attacked.
However, common sense tells you it wouldn't be a good idea.
How many parents risk letting their daughter out on their own late at night?
Not many.
The fact the Government did nothing in the face of all this, tells you there's an ulterior motive.
Of course, the real reason in this case why the import of trees was not banned, was because the E.E.C. would simply not have allowed it and they know it.
They would have threatened Britain with legal action, called it discrimination, attacked British interests and boycotted our exports.
There would have been hell to pay.
Constant bleating of the mantra of an 'evidence led policy' is a red herring, thrown in to muddy the waters.
The Ash die back example demonstrates both the way statistics, as the required evidence, are used to deny a common sense approach and/or all other concerns to influence decisions and the way that through this ruse what was after all sound, obvious advice, can be ignored.
Thus, cover for inaction was provided and this subsequent duplicity thereby avoided the Government having to admit the awkward, politically sensitive and embarrassing fact that, because of the E.E.C. they were impotent and indeed simply could not act.
The next time you are presented with some statistics, think for yourself.