by only not be used;one letter,so some letters will > Each correct answer carries [5 marks], and you do not have to provide any justification for the answer given; D All the symbols refer to the notation used throughout the module's lectures and lecture slides. (i) Classical Linear Regression Model (CLRM) [ ] (ii) Sum of Squared Residuals (SSR) (iii) Central Limit Theorem (CLT) (iv) sample regression equation (v) multicollinearity (A) variation in Y not explained by the fitted model; (B) estimation method based on the criterion of minimising the sum of squared residuals; (C) variation in Y not explained by its sample mean Y; \text { (D) represented by: } \hat{Y}_{i}=b_{0}+b_{1} X_{i} \text {; } \text { (E) represented by: } Y_{i}=b_{0}+b_{1} X_{i}+e_{i} \text {; } (F) problem with the OLS estimates if some or all of the explanatory variables are highly correlated with each other; population regression equation with associated assumptions about the probability structure of its random components; ) problem with the OLS estimators when we exclude explanatory variables that should be present in the regression and which are also correlated with the included regressors; or a random sample of size n, when n is sufficiently large, the sampling distribution of X is approximately Normal with mean u and variance sigma2/n.
Fig: 1
Fig: 2
Fig: 3
Fig: 4
Fig: 5
Fig: 6
Fig: 7
Fig: 8
Fig: 9
Fig: 10
Fig: 11
Fig: 12
Fig: 13
Fig: 14
Fig: 15
Fig: 16
Fig: 17
Fig: 18