题目
1.一元线性回归模型y_(i)=b_(0)+b_(1)x_(i)+mu_(i)中，b_(1)的普通最小二乘估计为（）A. hat(b)_(1)=(sum xy)/(sum x^2)B. hat(b)_(1)=(sum(x-bar(x))(y-bar(y)))/(sum(x-bar(x))^2)C. hat(b)_(1)=(sum(x-bar(x))y)/(sum(x-bar(x))^2)D. hat(b)_(1)=(nsum xy-sum xsum y)/(nsum x^2)-(sum x)^(2)
1.一元线性回归模型$y_{i}=b_{0}+b_{1}x_{i}+\mu_{i}$中，$b_{1}$的普通最小二乘估计为（）
A. $\hat{b}_{1}=\frac{\sum xy}{\sum x^{2}}$
B. $\hat{b}_{1}=\frac{\sum(x-\bar{x})(y-\bar{y})}{\sum(x-\bar{x})^{2}}$
C. $\hat{b}_{1}=\frac{\sum(x-\bar{x})y}{\sum(x-\bar{x})^{2}}$
D. $\hat{b}_{1}=\frac{n\sum xy-\sum x\sum y}{n\sum x^{2}-(\sum x)^{2}}$
题目解答
答案
BD
B. $\hat{b}_{1}=\frac{\sum(x-\bar{x})(y-\bar{y})}{\sum(x-\bar{x})^{2}}$
D. $\hat{b}_{1}=\frac{n\sum xy-\sum x\sum y}{n\sum x^{2}-(\sum x)^{2}}$
B. $\hat{b}_{1}=\frac{\sum(x-\bar{x})(y-\bar{y})}{\sum(x-\bar{x})^{2}}$
D. $\hat{b}_{1}=\frac{n\sum xy-\sum x\sum y}{n\sum x^{2}-(\sum x)^{2}}$