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政治大學中山所共同選修 課程名稱: 社會科學計量方法與統計-計量方法 Methodology of Social Sciences 授課內容: Inference in the Simple Regression Model 日期: 2003 年 10 月日.

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Presentation on theme: "政治大學中山所共同選修 課程名稱: 社會科學計量方法與統計-計量方法 Methodology of Social Sciences 授課內容: Inference in the Simple Regression Model 日期: 2003 年 10 月日."— Presentation transcript:

1 政治大學中山所共同選修 課程名稱: 社會科學計量方法與統計-計量方法 Methodology of Social Sciences 授課內容: Inference in the Simple Regression Model 日期: 2003 年 10 月日

2 政治大學 中山所共同選修 黃智聰 b~N(β, σ b 2 ) Z= ~N(0,1) Chi-square random variable arise when standard normal, N(0,1), random variables are squared. If Z~N(0,1) and V~x 2 (m) and if Z and V are independent, then m is the degree of freedom i=1,2 we estimated variance unknown

3 政治大學 中山所共同選修 黃智聰 P(t ≧ t c )=P(t ≦ t c )=α/2 P(- t c ≦ t ≦ t c )=1-α P[- t c ≦ ≦ t c ]=1-α P[b 2 - t c Se (b 2 ) ≦ β 2 ≦ b 2 + t c Se(b 2 ) ]=1-α The interval endpoints, and both b 2 and Se(b 2 ) are random variables, since their values are not known until a sample of data is drawn. b 2- β 2 Se( b 2 )

4 政治大學 中山所共同選修 黃智聰 b 2 ± t c Se(b 2 ) is call a (1- α) ×100% interval estimate of β 2 or called a (1- α) ×100% confidence interval. (1- α) ×100% of all the interval constructed would contain the true parameter β 2. This we known before any data are actually collected. If the interval is [0.0666,0.1900], is β 2 in the interval? We don ’ t known, and we will never known!! We just know 95% of all the interval estimates constructed using this procedure will contain the true parameter.

5 政治大學 中山所共同選修 黃智聰 5.2 Hypothesis Testing Components of Hypothesis Tests 1.A Null hypothesis, H 0 2.An alternative hypothesis, H 1 3.A test statistic 4.A rejection region

6 政治大學 中山所共同選修 黃智聰 1. H 0 : β 2 =c, c is a constant, and is an important value in the context of special regression model. 2. H 1 : β 2 ≠ c H 1 : β 2 > c b/c theoretically, β 2 can not be negative H 1 : β 2 < c when there is no chance that β 2 > c

7 政治大學 中山所共同選修 黃智聰 3.The test statistic Ex: H 0 : β 2 =c, β 1 ≠ c Therefore don ’ t have standard normal distribution and the formation of a t random variable. b 2 -c Var(b 2 )

8 政治大學 中山所共同選修 黃智聰 The rejection Region The rejection region is the range of values of the test statistic that leads to rejection of the null hypothesis. ie: when the null hypothesis is true, are unlikely and have low probability. Two-tailed Test If the value of the test statistic falls in the rejection region, either tail the t-distribution, then we reject the null hypothesis and accept the alternative. Avoid sampling that we accept the null hypothesis instead of saying we fail to reject the null hypothesis

9 政治大學 中山所共同選修 黃智聰 Format for Testing Hypothesis 1.Determine the null and alternative hypothesis 2.Specify the test statistic and its distribution if the null hypothesis is true. 3.Select α and determine the rejection region 4.Calculate the sample values of the test statistic 5.State your conclusion

10 政治大學 中山所共同選修 黃智聰 5.2.6 Type I and Type II errors 5.2.7 The P-value of A Hypothesis Test T=0.9263 If P < α then the test procedure leads to rejection of the null hypothesis 5.2.8 A significance Test in the Food Expenditure Model A statistically significant relationship exists b/w x and y. If α more likely to reject H 0 How to choose α 0.1, 0.05, 0.01

11 政治大學 中山所共同選修 黃智聰 5.2.10 One-tailed Test H 0 : β k =c H 1 : β k < c or β k > c 電腦是以 One-tailed 來算 因為 if two-tailed 算出 P=0.08 one-tailed P=0.04 所以在 two-tailed at α=0.05 時 reject H 0 But one-tailed can ’ t reject H 0


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