Statistics
are a popular source
in examination papers. Whether primary sources produced in the
past e.g. census returns, or secondary sources produced after
some serious hard work by historians, statistics
can provide important scientific support for general conclusions
we may wish to make.
The study of history which places particular
emphasis on statistical or quantitative methods is known as
cliometrics.
Strengths
Limitations
Statistics are often the end result of a lot of hard
work, serious research and counting. They can summarize very
accurately and with great precision very complex factors. Rather
than vague suggestions that there was a ‘big increase’ or ‘many
casualties’ it is far better to have an exact figure. For example,
how many newspapers, schools or libraries in a town can tell us
something about literacy levels, especially when we compare one town
with another or the same over a period of time. Statistics are
therefore great for making comparisons over time and space.
From numbers we can generate graphs that demonstrate correlation,
patterns and trends. From these we can propose reasons for
historical causes and consequences or relative significance. For
example, I think that unemployment was an important factor in the
rise to power of the Nazi party in Germany. My conclusion is
supported by the statistical evidence that shows a correlation
between numbers unemployed and the number of people who voted for
the Nazis.
The American writer Mark Twain famously said ‘There
are three kinds of lies: lies, damned lies, and statistics.’ Because
they improve the power of argument, it is tempting use statistics
selectively in order to make a point. To say that ‘most statistics
are made up’ is less impressive than ‘51.73% of statistics are made
up’! Somehow, numbers just seem more 'scientific'.
Because statistics are only the end result of research, we are not
always aware of the methods that were used to arrive at the figures.
It is very important to know who conducted the research and how. In
totalitarian regimes, with strict control over information,
statistics are notoriously unreliable. And even in more liberal
regimes, surveys can be conducted with the intention of arriving at
a particular conclusion. The official surveys of child labour in
19th century England asked children ‘leading’ questions in order to
demonstrate how awful conditions were. (see below)
Other than accuracy, the main issue with statistics is the question
of how representative they are. This is particularly true of
percentages. ‘33% of history teachers in my school are Welsh’ sounds
like a lot, but are hardly representative if I’m the only one.
Typically on an exam paper a source of statistics only provide
information for an aspect of the question– one time or one place -
where as the question invariably is more general.
In the end statistics are just numbers and not everything important
about the past can be conveyed by numbers.
Statistics for World War Two casualties are
difficult to verify and vary from source to source.
These figures are taken from a BBC website and the
author acknowledges that they can only be
approximate.
Discussion Points: Why is it difficult
for historians to agree on accurate statistics of
World War Two casualties?
What do the statistics
tell you about War as experienced in Eastern and
Western Europe?
How are statistics generated? Looking behind the numbers.
Report of the Select
Committee of Factory Children's Labour, 1831-32. Interview with
Charles Burns, a 14 year old textile worker in Leeds.
At what age did you begin work in the mills? I was
nearly eight years old.
What were your hours of working? From half past five in the
morning till eight at night. How often were you allowed to make
water [go to the toilet]? Three times a day. Could you hold
your water [urine] all that time? No. We were forced to let it
go.
Did you spoil and wet your clothes constantly? Every noon and
every night.
Did you ever hear of that hurting anybody? Yes, there was a boy
died.
Did he go home ill with attempting to suppress his urine? Yes,
and after he had been home a bit, he died.
Were you beaten at your work? If we looked off our work or spoke
to one another we were beaten. What time of day was it you were
most beaten? In the morning.
And when you were sleepy? Yes. Was the mill very dusty?
Yes.
What effect did it produce? When we went home at night and went
to bed we spit up blood. Had you a cough with inhaling the dust?
Yes, I had a cough and spit blood.
This survey provides good examples of 'leading
questions', where those conducting the survey ask questions designed
to produce certain kinds of answer.
