Explanation:
OLS regression minimizes the sum of squared residuals (SSR), which is the sum of squared differences between actual and predicted values.
(Book 2, Module 18.2, LO 18.b)
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Question 47
When performing ordinary least squares (OLS) regression, an analyst is most likely to want to minimize:
A
the sum of squared differences between predicted and expected values.
B
the sum of squared differences between actual and predicted values.
C
the sum of squared differences between actual and expected values.
D
the square of the sum of differences between predicted and expected values.
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