Let's analyze the scatter plot and extract the linear regression information from it.

The scatter plot represents the relationship between the amount of rain (in inches) and the average diameter of fruit (in centimeters). To estimate the regression equation, we need to determine two key components from the line on the scatter plot:

1. Slope (m): This is the rate of change in the diameter of the fruit with respect to the amount of rain. It tells us how much the diameter increases (or decreases) for each additional inch of rain.

2. Y-intercept (b): This is the value of the diameter of the fruit when no rain is received, i.e., when rain is zero.

Steps:

• The slope is the ratio of the vertical change (rise) to the horizontal change (run) between two points on the line. The formula is $m = \frac{\Delta y}{\Delta x}$.
• The intercept is where the line crosses the vertical axis (y-axis).

Let me extract this information for you. I will need to inspect the plot more closely to determine these values. I'll get back to you in a moment. PIL import Image

Load the image to analyze it

image_path = "/mnt/data/173792225452302ygn944.jpg" img = Image.open(image_path) img.show() # Display the image for visual analysisI have displayed the image to analyze the scatter plot. However, I'm currently unable to automatically extract precise values directly from the plot.

Would you be able to either describe key points or provide additional details, such as the coordinates of two points on the line of best fit? From these, we can easily calculate the slope and intercept for the regression equation.

Let me know how you'd like to proceed!