Hypothesis testing
Hypothesis testing
asks how unusual it is to
get data that differ from the null hypothesis.
If the data would be quite unlikely under H
0
,
we reject H
0
.
So we imagine making an
infinite number of samples,
from a distribution where men
and women have the same
height.
Hypothesis testing in a nutshell
Population
We want to know something
about this population, say, are
men and women the same
height, on average?
We can't measure everyone it
would take too long and cost
too much. So we take a sample,
and meaure those. For these
we estimate the difference
between men and women's
mean height.
Sample
But we have a problem:
The sample doesn't have the same
properties as the population,
because of chance errors.
So we need to know how good the
sample is, and how likely it is that it is
much
different from the population.
We make an estimate from each of
these samples, and from these we can
So we imagine making an
infinite number of samples,
from a distribution where men
and women have the same
height.
So we need to know how good the
sample is, and how likely it is that it is
much
different from the population.
We make an estimate from each of
these samples, and from these we can
calculate the sampling distribution of
the estimate.
Frequency
Difference in mean height
If the actual sample value is so
different from what we would expect
samples to look like, then we can
say that the men in this population
are on average taller than the
women.
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 Spring '10
 Driscoll
 Statistics, Null hypothesis, Statistical hypothesis testing

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