In his statistics class, Sam said, "Linear regression model is a tool to predict the relationship between the dependent variable, and independent variable. So, there will be one specific linear regression model that I can use to know the relationship of variables. I decided to use ordinary least square to have the best estimates for linear regression model parameters because ordinary lease square makes me find the linear regression equation with minimum average of difference between actual dependent variable and the value predicted by linear regression model." Is Sam correct? If not, how do we need to fix his idea?
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