Praveen_India
Member
Hi,
Reference: R11. P1.T2_Stock_v5
The three key assumptions of the ordinary least squares (OLS) linear regression model are the following:
1. Assumption # 1: The conditional distribution of the error term, u(i), has a mean of zero. This assumption is a formal mathematical statement about the “other factors” contained in the error term and asserts that these other factors are unrelated to the independent variable, X(i), in the following sense: given a value of X(i), the mean of the distribution of these other factors is zero.
Please can you explain the underlined statements. I understood that there should not be any relationship between u and X but the explanation given in terms of Distribution and Mean is something I am not able to understand.
Thanks,
Prveen
Reference: R11. P1.T2_Stock_v5
The three key assumptions of the ordinary least squares (OLS) linear regression model are the following:
1. Assumption # 1: The conditional distribution of the error term, u(i), has a mean of zero. This assumption is a formal mathematical statement about the “other factors” contained in the error term and asserts that these other factors are unrelated to the independent variable, X(i), in the following sense: given a value of X(i), the mean of the distribution of these other factors is zero.
Please can you explain the underlined statements. I understood that there should not be any relationship between u and X but the explanation given in terms of Distribution and Mean is something I am not able to understand.
Thanks,
Prveen