Lecture Outline 本课提纲nCLM assumptions and Sampling Distributions of the OLS Estimators经典假设与OLS估计量的样本分布nBackground review of hypothesis testing假设检验的背景知识nOne-sided and two-sided t tests单边与双边t检验nCalculating the p values计算p值Assumption MLR.6(Normality)假设MLR.6（正态）n So far,we know that given the Gauss-Markov assumptions,OLS is BLUE,我们已经知道当我们已经知道当GaussMarkov假设成立时，假设成立时，OLS是最优线性是最优线性无偏估计。无偏估计。n In order to do classical hypothesis testing,we need to add another assumption(beyond the Gauss-Markov assumption
