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The linear regression model is defined to be of \(y = \alpha_0 + \alpha_1 x + \epsilon\)
The variance of a given population \(\{ x_1, x_2, \cdots, x_{15}, \cdots, x_n \}\) is given by
\[ \sigma^2= \frac{\sum_{i = 1}^n(x_i-\mu)^2}{N}. \]
The Pearson correlation coefficent is given by
\[ r=\frac{\sum_{i=n}^n(x_i-\bar{x})(y_i-\bar{y})}{\sqrt{(x_i-\bar{x})^2} \times\sqrt{(y_i-\bar{y})^2}} \]
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