Exam2_FC

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F(x) Y
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Dependent, explained, or response variable. Independent, explanatory, or predictor variable.
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A B
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Slope coefficient. Y-intercept (constant).
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Y Y i
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Actual observation, usually obtained from a sample. Forecasted (expected) value.
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Zero - Yi Y
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Residual error ( ei ): Sum of residual values.
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Normalization Minimum Value
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The sum of residual values squared. Compare two dissimilar things (i.e. liters to pounds).
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Residuals Least Squares
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= ei 0 and = ei2 MIN Believed to be caused by omitted variables.
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Predictability Residuals
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Measures outside influence or unpredictability to the model. Becomes smaller as the residuals become bigger
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Sum of Squares Due to Error (SSE) Sum of Squares Due to Error (SSE)
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Measures the changes in Y caused by variables omitted from the model; measures the unpredictability of the model. ei2
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Sum of Squares Total (SST) Sum of Squares Regression (SSR)
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Measures the changes in Y caused by variables within the model; measures the predictability of the model. Measures all changes in Y regardless of the cause.
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SSR; SSE SSR + SSE
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SST equation. ____ are variables within the model and ____ are variables outside the model.
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Coefficient of Determination = R2 SSRSST
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Coefficient of Determination: Answers the question, how predictable is the model?
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SSR = SST; SSE = 0 SSR = 0; SST = SSE
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explanation lies outside the model. All explanation to the
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