Regression analysis consists of two major tasks: (i) estimation of population parameters and (ii) hypothesis testing...

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Regression analysis consists of two major tasks: (i) estimationof population parameters and (ii) hypothesis testing (e.g., t-test,F-test) or the application of inferential statistics to theestimated parameters. We learned OLS (ordinary least square)principle as the major estimation tool (thereby fulfilling thefirst task). There is a critically important assumption that wehave to make in order to perform the second task (that is, toconduct hypothesis testing with respect to estimated parameters).Identify and discuss it. (10 points)

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We derive tests about the coefficients of the normal linearregression model In this model the vector of errors is assumed tohave a multivariate normal distribution conditional on with meanequal to and covariance matrix equal to where is the identity matrix and is a positiveconstantIt can be proved see the See Answer

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