第二章 一元线性回归的检验和预测2011.pptVIP

第二章 一元线性回归的检验和预测2011.ppt

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第二章 一元线性回归的检验和预测2011

Hypothesis test: Is a given observation or finding sufficiently closed to hypothesized value so that we can’t reject the stated hypothesis? There’re two approaches to proceed the hypothesis test: test of significance and confidence interval α: level of significance,fixed (1- α)%: confidence df: degree of freedom Critical value P-value:probability actual probability of obtaining a value of T-TEST as much as or greater than obtained in OLS estimation If fixed αis greater than P, we may reject the null hypothesis. 2.2 the analysis of variance 2.5 report and analysis of the result of regression Analysis: 1、Are the signs of estimated regression coefficient accordance with our expectation or economic theory? 2、Is the slope coefficient statistical significant? (statistically significantly different from Zero.) 3、How well does the regression model explain the change or variation of Y? If R2 is great enough ,we can say that the regression model seems quite good. 4、Is our model satisfied the normality assumption ? * * CHAPTER TWO HYPOTHESIS TESTING OF TWO-VARIABLE LINEAR REGRESSION MODEL 2.1 test of significance and confidence interval 2.1.1 test of significance Constituting standardized normal distribution But to obtain , we need Usually , true is unknown, now we substitute for . Furthermore we substitute for and get a t-statistic 1、Put forward hypothesis: Null hypothesis:H0: Alternative hypothesis:H1: 2、Constitute t-statistic and compute the value of T: 3、Decision rule: If |T| ta/2(n-2),reject the H0, , it means that the explanatory variable indeed infects dependent variable. The variable X is statistically significant . Otherwise, accept H0,it indicates that there isn’t significant correlation between explanatory and dependent variable supplement:decision rule of t-test T -tα β1 < β1* β1≥ β1* 左尾

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