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The 31st World University Summer Games will be held in Chengdu from July 28 to August 8, 2023, promoting sports for all. A sports equipment store has compiled data on the sales volume $y$ (in units of thousand sets) and the selling price $x$ (in units of yuan) of sports equipment from January to May 2023, as shown in the table below:

| Month | 1   | 2   | 3   | 4   | 5   |
|-------|-----|-----|-----|-----|-----|
| $x$   | 100 | 90  | 80  | 70  | 60  |
| $y$   | 5   | 7.5 | 8   | 9   | 10.5|

$(1)$ Calculate the correlation coefficient $r$ of $(x_i, y_i)$ for $i=1,2,3,\cdots,n$, and determine if there is a strong linear correlation between the sales volume $y$ and the selling price $x$ (When $|r|\in [0.75,1]$, it can be considered as a strong linear correlation; otherwise, there is no strong linear correlation) (Round to $0.001$);<br/>$(2)$ Establish the linear regression equation of $y$ with respect to $x$ (Round to $0.001$), and estimate the sales volume when the selling price of the equipment is $50$ yuan.

Reference formula: For a set of data $(x_i, y_i)$ for $i=1,2,3,\cdots,n$, the correlation coefficient $r$ is calculated as $r=\frac{\sum_{i=1}^{n}(x_{i}-\overline{x})(y_{i}-\overline{y})}{\sqrt{\sum_{i=1}^{n}(x_{i}-\overline{x})^{2}}\sqrt{\sum_{i=1}^{n}(y_{i}-\overline{y})^{2}}}$, and the least squares estimates of the slope and intercept of the regression line $\hat{y}=\hat{b}x+\hat{a}$ are $\hat{b}=\frac{\sum_{i=1}^{n}(x_{i}-\overline{x})(y_{i}-\overline{y})}{\sum_{i=1}^{n}(x_{i}-\overline{x})^{2}}$ and $\hat{a}=\overline{y}-\hat{b}\overline{x}$, with reference data: $\sqrt{16500}\approx128.452$.

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