Final answer:
To identify extreme points, a scatter plot is graphed along with a best-fit line and two additional lines. In the given dataset, after graphing, the point (65, 175) is identified as the only outlier, as it is more than two standard deviations away from the best-fit line, making it one extreme point.
Step-by-step explanation:
The question seems to ask about the identification of extreme points in a statistical or mathematical context. In statistics, an extreme point, or outlier, is a data point that is significantly distant from the other points in the dataset.
Based on the provided information, it sounds like the process described involves graphing data on a scatter plot, fitting a line to the data, and identifying points that might not fit the general pattern of the data, often by analyzing how far they are from a computed best-fit line.
In this case, you are advised to graph the scatter plot and add two extra lines (Y2 and Y3) to help visualize the potential outliers. By following the instructions, you will identify that the point (65, 175) is an outlier.
It's described as being outside of the two extra lines you entered and more than two standard deviations away from the best-fit line. Hence, in the data provided, there is one extreme point.