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Part IV: Guesstimating and Hypothesizing with Confidence
in the dark. Here are some examples of estimates that I came across in one
single issue of a leading business magazine. They come from a variety of
sources:
✓ Even though some jobs are harder to get these days, some areas are
really looking for recruits: Over the next eight years, 13,000 nurse anes-
thetists will be needed. Pay starts from $80,000 to $95,000.
✓ The average number of bats used by a major league baseball player per
season is 90.
✓ The Lamborghini Murcielago can go from 0 to 60 mph in 3.7 seconds
with a top speed of near 205 miles per hour.
Some of these estimates are easier to obtain than others. Here are some
observations I was able to make about those estimates:
✓ How do you estimate how many nurse anesthetists are needed over the
next eight years? You can start by looking at how many will be retiring
in that time; but that won’t account for growth. A prediction of the need
in the next year or two would be close, but eight years into the future is
much harder to do.
✓ The average number of bats used per major league baseball player in a
season could be found by surveying the players themselves, the people
who take care of their equipment, or the bat companies that supply
the bats.
✓ Determining car speed is more difficult but could be conducted as a test
with a stopwatch. And they should find the average speed of many dif-
ferent cars (not just one) of the same make and model, under the same
driving conditions each time.
Not all statistics are created equal. To determine whether a statistic is reliable
and credible, don’t just take it at face value. Think about whether it makes
sense and how you would go about formulating an estimate. If the statistic is
really important to you, find out what process was used to come up with it.
(Chapter 16 handles all the elements involving surveys, and Chapter 17 gives
you the lowdown on experiments.)

Linking a Statistic to a Parameter

A parameter is a single number that describes a population, such as the
median household income for all households in the U.S. A statistic is a single
number that describes a sample, such as the median household income of
a sample of, say, 1,200 households. You typically don’t know the values of
parameters of populations, so you take samples and use statistics to give
your best estimates.

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