In the graph provided, the large blue point represents a data point that is treated separately for comparison. The red dashed line shows the least-squares regression line excluding the blue point, while the solid blue line represents the least-squares regression line with the blue point included.

To determine whether the point in blue is influential, we need to assess how much the blue point affects the slope and intercept of the regression line. Based on your image:

• If the blue point had a significant impact, the two regression lines (red dashed and blue solid) would differ greatly.
• If the lines are similar, then the point does not have a major influence.

From the image, it appears that the two lines have a noticeable shift, especially in their slopes. Therefore, the blue point does significantly affect the regression line, indicating that it is influential.

Thus, the correct answer is:

(2) Yes, because the point significantly affects the least-squares regression line.

Would you like further details or explanations on this?

Here are five related questions you might find helpful:

1. What is an influential point in regression analysis?
2. How do outliers affect the least-squares regression line?
3. What statistical methods can detect influential points?
4. How is the residual value connected to identifying influential points?
5. What are some ways to handle influential points in data?

Tip: Always plot your data and compare regression models with and without potential outliers to determine their influence!