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is likely to change the regression model substantially all by itself.
Adjusted R2
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permits a more equitable comparison between models of different sizes.
You can use it to help you decide whether to accept a new model or not.
,indicator variables
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Each location has a different intercept, but they all have the same slope
interactions
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have different slopes and different intercepts
equal variance assumption
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the variability of y should be about the same for all values of x
regression equation
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intercept coefficient + independent variable coefficient(x)
, Larger SSR means
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our model accounts for a large portion of the variability in y
When the data can be divided into two groups with similar regression slopes
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we can incorporate the group information into a single regression model.
quadratic terms
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The scatterplot of the relationship between the two variables is not linear.
There is a curve.If we look at the
Residual plot, we see it doesn't look random, and there isa pattern to the
residuals.
how to tell if it has a large residual
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