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Parameter: A number that describes the population.
Statistic: A number that can be computed from the sample data without making use of any
unknown parameters.
Remember s and p: statistics come from samples, and parameters come from populations.
μ: mean of a population
: mean of a sample
The sample mean
from a sample or an experiment is an estimate of the mean μ of the
underlying population.
Probability model: A mathematical description of a random phenomenon consisting of two parts:
a sample space S and a way of assigning probabilities to events.
If we keep on taking larger and larger samples, the statistic
is guaranteed to get closer and
closer to the parameter μ. If we can afford to keep on measuring more subjects, eventually we
will estimate the mean odor threshold of all adults very accurately. This remarkable fact is called
the law of large numbers. It is remarkable because it holds for any population.
Law of large numbers: Draw observations at random from any population with finite mean μ. As
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 Winter '11
 PattiColling
 Statistics

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