Linear Regression about SSR I've studied about Anova.
But I wonder 
$$SSR=\sum_{i=1}^{30}(\hat{y}_i-\bar{y})^2=(b_1)^2\sum_{i=1}^{30}(x_i-\bar{x})^2$$
In this equation, why does $(b_1)^2$ appear?? and how to tranform summation about y to it about x?
And finally Why do they use $b_1$ instead of $β_1$

Are you sure that this is the sum of squares of residuals?  I would have expected $\displaystyle \sum_{i=1}^{30}(y_i - \hat{y}_i)^2$
Meanwhile you have something like $\hat{y}_i= b_0 + b_1 x_i$ and  $\bar{y}=b_0 + b_1 \bar{x}$ from your linear regression, so $\hat{y}_i-\bar{y}=b_1(x_i-\bar{x})$, giving $$\displaystyle \sum_{i=1}^{30}(\hat{y}_i-\bar{y})^2 = \sum_{i=1}^{30}(b_1(x_i-\bar{x}))^2 = b_1^2 \sum_{i=1}^{30}(x_i-\bar{x})^2$$ but this is what I would expect ANOVA to call the sum of squares of treatment
