A very small dataset with two variables is as following x12 3 4 5 10 Suppose the regression line is y-a+bx a). Find the value of b. b). Find the value of a. c). From computer, we find, SSR-4.9, S...
Given are five observations for two variables, 7 and y. 2 1 3 4 S M 3 7 5 11 14 The estimated regression equation is y = 0.2 +2.67 a. Compute the mean square arror using the following equation to 3 decimals), - MSE SSE - 2 b. Compute the standard error of the estimate using the following equation (to 3 decimals). 5 VMSE SSE N-2 c. Compute the estimated standard deviation by using the following equation (to 3...
3) Consider the following linear regression: y =a + Bx + Show that minimizing the sum of squared residuals ( - ) to obtain OLS estimators of the slope and the intercept results in the following algebraic properties a) b) Ex = 0 = 0 4) You run the following regression: TestScore = a + (Female) + where TestScore is measured on a scale from 400 to 1000, and female is an indicator for the gender of the student. You...
Given are five observations for two variables, r and y. 3 4 5 1 2 7 6 11 14 4 The estimated regression equation is y = 1.2 + 2.4r Compute the mean square error using the following equation (to 3 decimals). a. SSE s2=MSE n- 2 decimals). b. Compute the standard error of the estimate using the following equation (to SSE VMSE Vn-2 SE c. Compute the estimated standard deviation bi using the following equation (to 3 decimals). Sp...
5. Summary of regression between a dependent variable y and two independent variables X, and x2 is as follows. Please complete the table: SUMMARY OUTPUT Regression Statistics Multiple R 0.9620 R Square R2E? Adjusted R Square 0.9043 Standard Error 12.7096 Observations 10 ANOVA F Significance F F=? Overall p-value=? Regression Residual Total 2 df of SSE MS MSR=? MSE? 14052.1550 1130.7450 SSTE? MSE? 9 Coefficients -18.3683 Standard Error 17.9715 t Stat -1.0221 Intercept ty=? 2.0102 4.7378 0.2471 0.9484 P-value 0.3408...
Given are five observations for two variables, and y 3 6 14 16 19 yi 52 57 42 17 10 Use the estimated regression equation is ý 67.97 - 2.79z a. Compute the mean square error using equation SSE MS2 (to 2 decimals) b. Compute the standard error of the estimate using equation. SSE n -2 (to 2 decimals) c. Compute the estimated standard deviation of bi using equation (to 4 decimals) d. Use the t-test to test the following...
For this exercise we will run a regression using Swiss demographic data from around 1888. The sample is a cross-section of French speaking counties in Switzerland This data come with the R package datasets. The first step is to load the package into your current environment by typing the command libraryldatasets) in to the R console. This loads a number of datasets including one called swiss. Type help/swiss) in the console for additional details. The basic variable definitions are as...