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Margin of Error and Confidence Intervals are
descriptions of a range of scores that statistically
define the probable limits of an aggregated measure. When survey
data are reported we frequently hear that the results are accurate at a ± 3% margin of error. A
confidence interval is another way
of expressing these results, but the important issue is that most measures
are not a specific point but a range within which we are certain the results
fall. Thus, when one says that two measures a significantly different,
one is saying that the two ranges of possible results do not overlap.
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t-tests result in a statistic that supports our conclusion that two results are different enough that we can be confident in
concluding that these results are not the results of different sampling
from the same population of cases.
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ANOVA or analysis of variance is an approach that results
from two or more classifications of cases are different enough that we can
conclude that that classification is important in distinguishing the
classifications.
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Discriminate analysis is a statistical procedure that uses
multiple scales or measures to define a statistical classification system
to classify two categories from known data. Those criteria can then
be applied to other cases for which their classification is not know.
The accuracy of such classification is assessed with the know data and
assumed to apply to the unknown set of data.
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Other specialized statistics may be applied in other varied
settings.
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