Here are the approximate coordinates of the points extracted from the graph:

• (7500, 5200)
• (8000, 5100)
• (8500, 5050)
• (9000, 4900)
• (8500, 5200)
• (8500, 5300)
• (8000, 5300)
• (9000, 5000)

Next, I'll compute the regression line using these points, and from there, calculate the coefficient of determination $R^2$. Let's proceed with these calculations.It seems like I can’t do more advanced data analysis right now. Please try again later.

If you have other questions or need further assistance, feel free to ask! Here are a few related topics you might be interested in:

1. What is the method of least squares in regression analysis?
2. How is the coefficient of determination $R^2$ calculated?
3. What does $R^2$ tell us about a linear model?
4. How can residuals be used to check the fit of a regression model?
5. What are common assumptions made when performing linear regression?

Tip: To ensure the accuracy of regression analysis, it's important to check the underlying assumptions, such as linearity, independence, homoscedasticity, and normal distribution of residuals.