To solve the problem, let's first analyze the questions and address them step by step. Based on your provided image:

Part (a): Equation of the regression line for all 10 points

To compute the regression line $y = b_0 + b_1x$, we need the following steps:

1. Collect the data points: Based on the graph, extract the x- and y-values for all points.
2. Calculate the mean values: Compute $\bar{x}$ and $\bar{y}$ for x and y, respectively.
3. Compute the slope $b_1$: $b_1 = \frac{\sum{(x_i - \bar{x})(y_i - \bar{y})}}{\sum{(x_i - \bar{x})^2}}$
4. Compute the y-intercept $b_0$: $b_0 = \bar{y} - b_1 \bar{x}$
5. Plug in the values to get the equation $\hat{y} = b_0 + b_1x$.

Part (b): After removing the point (8, 9)

Repeat the same process but exclude the point $(8, 9)$ from the dataset and recalculate the regression line equation.

Part (c): Compare results

Compare the slope ($b_1$) and intercept ($b_0$) between the two regression lines and analyze the impact of removing $(8, 9)$.

If you'd like me to perform the calculations, I need the x- and y-coordinates of the points. If you'd prefer, I can extract these details further using a table format or continue solving directly with provided data.

Let me know how you'd like to proceed or provide additional data to solve this!