Consider the multiple regression model shown next between the dependent variable Y and three independent variables X₁, X₂, and X₃, which result in the following function: For this model, there were 35 observations; SSR = 1400 and SSE = 600. Based on the information given, it can be concluded that: A) the coefficient of X₃ is significant. B) the regression model is not significant. C) the coefficient of X₁ is significant. D) the regression model is significant.

Question

Quizplus · Accepted Answer

Since we are given both SSR (sum of squares due to regression) and SSE (sum of squares due to error), we can calculate the total sum of squares: SST = SSR + SSE = 1400 + 600 = 2000 From this, we can calculate the R-squared value: R-squared = SSR/SST = 1400/2000 = 0.7 An R-squared value of 0.7 indicates a reasonably strong relationship between the independent variables and the dependent variable, so we can conclude that the regression model is significant. However, we cannot determine the significance of individual coefficients (such as X₁ or X₃) solely based on the given information.

Consider the Multiple Regression Model Shown Next Between the Dependent