Chapter 3
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Total sum of squares (TSS)
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Chapter 3
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Total sum of squares (TSS)
$$\sum_i (y_i - \overline{y})^2$$
measures total variance in the response \(Y\)
\(R^2\) statistic
$$\frac{\text{TSS} - \text{RSS}}{\text{TSS}} = 1 - \frac{\text{RSS}}{\text{TSS}}$$
measures the proportion of variability in \(Y\) that can be explained using \(X\)
Residual sum of squares (RSS)
$$\sum_i e_i^2$$
where \(e_i = y_i - \hat{y}_i\)
Residual standard error (RSE)
Estimate of \(\sigma\),
$$\sqrt{\frac{\text{RSS}}{n-2}}$$