The OLS residuals:
a. can be calculated using the errors from the regression function.
b. can be calculated by subtracting the fitted values from the actual values.
c. are unknown since we do not know the population regression function.
d. should not be used in practice since they indicate that your regression does not run through all your observations.

b. can be calculated by subtracting the fitted values from the actual values.

Step-by-step explanation:

OLS residuals -  it stands for ordinary least square. it is used to determine the missing value in the regression analysis. OLS works on one purpose that is to minimize the difference between the observed response and predict response.

The basic difference between Residual sum of square(RSS) and OLS is that RSS is used to predict how good is model while OLS  is considered as the method which is used to construct model>

okay wait before i answer, is this for your points on a graph?

d

step-by-step explanation:

i used the pitagoras theoreme