Final answer:
The sum of the squared residuals for the line y = 3x - 4 cannot be computed without concrete data points. Squared residuals are calculated for each data point, and outliers can significantly affect regression lines.
Step-by-step explanation:
To compute the sum of the squared residuals for the line y = 3x - 4, you need data points to evaluate actual y values versus predicted y values. The sum of the squared residuals is obtained by subtracting the predicted value from the actual value, squaring that result, and then summing these squares for all data points. Without data points being provided in the question, it's not possible to calculate the sum of the squared residuals for the line given.
In general, a squared residual for a given data point is calculated as (y - ŷ)2, where y is the actual value, and ŷ is the predicted value from our line of best fit. To identify outliers, like the student with exam scores of 65 and 175, residuals are compared to a threshold value which, in this context, is based on the standard deviation of the residuals. Data points with residuals outside of a certain range (e.g., greater than 32.8 or less than -32.8, as mentioned in the reference information) might be considered outliers and can impact the regression line.