| Statistics is a pain. Every normal person who takes
it knows that it is (almost always) badly taught,
unreadable, and even when you follow the idea, you
can't imagine where to apply it. It's hard to string the
ideas together. The assumptions are never true in
real life, and that seems to fill instructors with horror.
If it bothers the instructors, shouldn't it bother you? Statistical ideas are like rabbits. They are often used
as the show piece of magic acts. They are simple
animals - but not easy to grab hold of (particularly if
you're dropped in a whole field of them) and some
don't prove worth the effort. The minute you grab a
few they seem to multiply and then things are back
out of control again. It's a sad story. Why would
anybody bother?
The reason to learn this stuff is that it is terribly useful
in very practical ways. The difference between 50
and 100 plots may not seem important to someone
in a warm, dry office, but it matters to somebody on
a wet, cold, 60% slope. The reason to understand
this stuff is that it can save real money, real time and
real sweat
There is also a lot of good news about statistics:
Normal people can learn it, with little math
background or aptitude. It's true that many
statisticians are from mathematics
backgrounds, but it isn't necessary or useful
for most applications. Math people aren't
smart, they are just strangely wired and handle
equations easily. They are like musicians who
have "perfect pitch". It's a knack many of
them are born with, but it doesn't mean they
understand math - it's just easy for them to do
the mechanics. It often means that they can't
explain how to use statistics to normal (often
smarter) people. How could you "explain"
how to have perfect pitch? Just because you
can do it easily doesn't mean you can do it
usefully. Ordinary people who can see
statistics in perspective are often the most
innovative and credible users of statistics.
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Statistics has little to do with math. There are
some exact probabilities that are used, and
you may need math to calculate them, but this
is a detail. All the powerful ideas are logical
ideas. Stats is like legal evidence - the idea is
to examine pertinent, accurate evidence and
to weigh its value. Researchers spend lots of
time in the math details, but that end of the
work is not where the important ideas lie.
Calculators now do all the math, you only
have to work with the logical ideas.
There are only a few important ideas, even
though there are a mass of names and
symbols swirling around them. There are no
more than a handful of important equations
too, they just have lots of special forms. I
think we can straighten that out with
reasonable effort.
Your friends will like you anyway, even if you
do know how to do statistics. Such people
are even considered useful at times. A chain
saw is a lot more powerful tool than an axe,
so it's worth the effort to learn how it works
and how to use it safely. Besides, statistics is a
normal procedure many of you are expected
to know how to use. Just like driving a truck,
it's a necessary part of doing the job. Like
using a chain saw or juggling, it's a matter of
practice and the right approach. There are
plenty of ways to ease the pain. Over the next
few issues, we will be dealing with some of
the practical aspects of statistics like:
- How to get statistical help (instead of
just being a victim).
- "Distributions" and why most of them
don't matter.
- Averages, Standard Deviation,
Standard Error (and all those confusing
terms).
- Sample sizes and sampling error.
- Sample layout.
- We will also write up some advice on
choosing calculators to use and
personal computer programs that are
really useful and easy to get. Don't be
intimidated! Look at some of the
people that do this work - if they can
learn it, so can you.
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