Reciprocal Regression

Interpreting the Correlation Coefficient r
0.7＜|r|≦1 Strong correlation
0.4＜|r|＜0.7 Moderate correlation
　　0.2 < |r| < 0.4 Weak correlation
0 ≤ |r| < 0.2 No correlation

\(\normalsize\ Inverse\ regression\\ (1)\ mean:\ \overline{x^{\tiny -1}}={\large \frac{{\small \sum}{x_i^{\tiny -1}}}{n}},\hspace{10px}\bar{y}={\large \frac{{\small \sum}{y_i}}{n}}\\ (2)\ trend\ line:\ y=A+{\large \frac{B}{x}},\hspace{10px} B={\large\frac{Sxy}{Sxx}},\hspace{10px} A=\bar{y}-B\bar{x^{\tiny -1}}\\ \\ (3)\ correlation\ coefficient:\ r=\frac{\normalsize S_{xy}}{\normalsize \sqrt{S_{xx}}\sqrt{S_{yy}}}\\ \hspace{20px}S_{xx}={{\small \sum}(x_i^{\tiny -1}-\overline{x^{\tiny -1}})^2}={{\small \sum} (x_i^{\tiny -1})^2}-n \cdot \overline{x^{\tiny -1}}^2\\ \hspace{20px}S_{yy}={{\small \sum}(y_i-\bar{y})^2}={{\small \sum} y_i^2}-n \cdot \bar{y}^2\\ \hspace{20px}S_{xy}={{\small \sum}(x_i^{\tiny -1}-\overline{x^{\tiny -1}})(y_i-\bar{y})}={{\small \sum} x_i^{\tiny -1} y_i}-n \cdot \overline{x^{\tiny -1}}\bar{y}\\ \)