Regression analysis can best he described as A) a statistical technique tor dete

Question

Regression analysis can best he described as A) a statistical technique tor determining the true values of variables. B) a statistical technique for creating functional relationships among variables. C) a statistical technique for estimating the best relationship between one variable and a set of other selected variables. D) None of the above If a regression coefficient passes the t-test, it means that A) the regression equation is valid. B) the regression coefficient should be included in the regression equation. C) the regression coefficient can be used for forecasting. D) the regression coefficient is significantly different from zero. The coefficient of a linear regression equation indicates A) the percentage change in the independent variable relative to a unit change in the dependent variable. B) the change in the independent variable relative to a unit change in the dependent variable. C) the percentage change in the dependent variable relative to a unit change in the independent variable. D) the change in the dependent variable relative to a unit change in the independent variable. When of the following is a test of the statistical significance of the entire regression equation? A) t-test B) R^2 C) F-test D) Durbin-Watson test Which of the following is a measure of the explanatory power of the regression model? A) t-test B) R^2 C) F-test D) Durbin-Watson lest When the R^2 of a regression equation is very high, it indicates that A) there is a good chance of serial correlation and so the equation must be discarded B) all the coefficients are statistically significant. C) a high proportion of the variation in the dependent variable can be accounted for by the variation in the independent variables. D) the intercept term has no economic meaning. Which indicator shows how well a regression line fits through the scatter of data points? A) Durbin-Watson test B) t-test C) R^2 D) F-test

Explanation / Answer

1: C; because in regression we regress the response variable on other regressor

2: D; in t-test null hypothesis is "coefficient is 0" rejecting that means coefficient is different from 0

3: D

4: C

5: B

6: C

7: C

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