In the scatterplot shown, the task is to determine which point, if removed, would cause the y-intercept of the line of best fit to increase the most.

Here's the reasoning:

• The y-intercept is where the line crosses the y-axis. Points below the line tend to pull the y-intercept down, while points above the line push it up.
• Points far away from the trend of the line (outliers) have the most influence on both the slope and the y-intercept.
• Point D is significantly above the line and far from the rest of the points. If it is removed, the line will shift down, causing the slope to decrease, and thus the y-intercept will increase.

Thus, removing Point D would cause the y-intercept to increase the most.

The correct answer is D.

Would you like more details or have any questions?

Here are some related questions to consider:

1. How is the y-intercept calculated in a line of best fit?
2. What is the effect of removing outliers on the slope of a line?
3. How do different points influence the y-intercept based on their location relative to the line?
4. What is the general impact of high-leverage points on regression lines?
5. How does the removal of influential points affect predictions in regression analysis?

Tip: Outliers that are far from the line of best fit can drastically change the slope and y-intercept when removed.