1 Variance Inflation Factors can be used to detect Heterosc

___ 1. Variance Inflation Factors can be used to detect Heteroscedasticity problem in the regression analysis.

___ 2. The zero value of correlation coefficient (r ) indicates the absence of any relationship between two variables.

___ 3. A linear trend line can be obtained by using a least squares method rather than scatter diagram method.

___ 4. The coefficient of regression (parameter estimate) expresses the degree or strength of a linear relationship.

___ 6. Regression analysis measures the strength of the relationship between variables (i.e., independent and dependent)

___ 7. The condition known as multicollinearity occurs whenever one (or more independent variables) is (are) highly correlated with dependent variable.

___12. In the regression analysis, the dependent variable is used to predict the value of the independent variable(s).

___13. In a multiple regression analysis, it is possible for the value of coefficient of determination to be greater than one.

___14. The coefficient of determination can range only -1.0 to +1.0

___17. If H0: 1= 2= 3...k = 0 is rejected, then we can conclude that there is no linear relationship between Y and any of the K independent variables in the model (i.e., overall unreliability of regression model).

___18. A linear regression model that has more than one dependent variables is called multiple regression model.

___19. The ratio of unexplained variation to the total variations in the dependent variable which is explained by independent variables is called as coefficient of determination rather than as coefficient of correlation.

___21. In a multiple regression analysis, Y= b0 + b1X1 + b2X2, a home is recorded as X2 = 1 if it has an attached garage, X2 = 0 if it does not. In this study, X2 is a dummy variable.

___22. A value of less than 10 Variance Inflation Factor (VIF) indicates the existence of multicollinearity problem.

___23. The dummy variables can be used to represent both qualitative and quantitative characteristics of variables in The regression analysis.

___24. The partial correlation form, R Y X1. X2, means that the correlation between X1 and X2 after holding Y.

___25. Analysis of variance (F-ratio) can be used to test the overall significance of the multiple regression equation.

___27. One of the assumptions about multiple regression/correlation is that the errors are not correlated to each other. Violation of this assumption is referred to as a Autocorrelation.

___28. If the computed (or calculated )value of F-ratio is 11.5 and the critical (or tabulated) value is 5.8, we would accept the null hypothesis (Ho: 1=2=3=4=0).

___30. The adjusted R2 is always greater than the regular R2 in the multiple regression/correlation analysis because of its adjustment of both the number of independent variables and the sample size.

___ 32. Correlation coefficient of zero indicate the absence of any relationship between two variables. ___ 33. A linear trend line can be obtained by using a least square methods rather than scatter diagram method.

___ 35. The coefficient of determination equals the proportion of variation in Y that is unexplained by regression.

___ 36. The condition known as multicollinearity occurs whenever one or more independent variables are highly correlated with dependent variable.

____39. The coefficient of variation indicates the relative ratio of the expected value(mean) to the standard deviation

Solution

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THE SECOND STATEMENT IS FALSE AS  a correlation coefficient of zero (r=0.0) indicates the absence of a linear relationship and correlation coefficients of r=+1.0 and r=-1.0 indicate a perfect linear relationship.