00:01
Hey there, welcome to numerate.
00:04
So we are looking at regression analysis here, and we're asked to define the differences between the predicted y values and the actual y values.
00:15
All right, so the differences between the predicted y value and the actual y value, we can depict this as y minus y predicted.
00:27
Which basically signifies the error looking at the difference between the points and the line.
00:37
So, our answer is errors.
00:43
Question number two.
00:45
For a ols fits a line through sample data by.
00:51
So when we look at a regression analysis here, we are looking to minimize the sum of the squared deviations from the line.
01:01
Okay, so we're looking at minimizes the sum of square differences, which basically refers to choice and sum of squared differences is basically the sum of squared deviations.
01:41
So choice c should be our answer here...