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Stats: Regression
The idea behind regression is that when there is significant linear correlation, you can use a line
to estimate the value of the dependent variable for certain values of the independent variable.
The regression equation should only used
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When there is significant linear correlation. That is, when you reject the null hypothesis
that rho=0 in a correlation hypothesis test.
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The value of the independent variable being used in the estimation is close to the original
values. That is, you should not use a regression equation obtained using x's between 10
and 20 to estimate y when x is 200.
•
The regression equation should not be used with different populations. That is, if x is the
height of a male, and y is the weight of a male, then you shouldn't use the regression
equation to estimate the weight of a female.
•
The regression equation shouldn't be used to forecast values not from that time frame. If
data is from the 1960's, it probably isn't valid in the 1990's.
Assuming that you've decided that you can have a regression equation because there is
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 Spring '08
 AKBAS
 Statistics, Correlation

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