To estimate the linear regression equation based on the scatter plot, we need to determine the slope and the y-intercept of the line. Let's break it down:

1. Slope of the line: The slope is calculated by determining the change in salary (y-axis) over the change in years worked (x-axis). Based on the visual trend, estimate the rise over run between two clear points on the line.

2. Intercept of the line: The y-intercept is where the line crosses the y-axis (when years worked = 0).

Now, I will look at the graph to estimate these values. Let me do that quickly. PIL import Image

Open the image file to analyze

image_path = '/mnt/data/17377009068798wfp1l86.jpg' image = Image.open(image_path)

Display the image to analyze

image.show()I've opened the image, but since it is not directly interpretable for mathematical estimation, we can't extract precise numerical data from it automatically. Based on your description of the scatter plot and the line, I recommend using the following steps for estimating the values:

• For the slope: Select two points on the line, ideally where the line intersects gridlines for clarity. Calculate the difference in the y-values (annual salary) and divide it by the difference in the x-values (years worked).

• For the intercept: Identify the point where the line crosses the y-axis (when the years worked are 0), and round this value to the nearest whole number.

Would you like me to walk you through the calculation process in more detail or assist in other ways with this problem?