Answer To: 578Assignment-5 (Chs. 13 and 14)-solutions: Due by midnight of Sunday, April 26, 2013: drop box 4):...
David answered on Dec 22 2021
578Assignment-5 (Chs. 13 and 14)-solutions: Due by midnight of Sunday, April 26, 2013: drop box 4): 70 points (must show work when possible)
True/False(One point each)
Chapter 13
1. The standard error of the estimate (standard error) is the estimated standard deviation of the distribution of the independent variable (X). TRUE
2. In a simple linear regression model, the coefficient of determination only indicates the strength of the relationship between independent and dependent variable, but does not show whether the relationship is positive or negative. TRUE
3. When using simple regression analysis, if there is a strong correlation between the independent and dependent variable, then we can conclude that an increase in the value of the independent variable causes an increase in the value of the dependent variable. FALSE
4. The error term is the difference between an individual value of the dependent variable and the corresponding mean value of the dependent variable. TRUE
5. In bi-variate regression the Coefficient of Determination is always equal to the square of the correlation coefficient. TRUE
6. In Regression Analysis if the variance of the error term is constant, we call it the Heteroscedasticity property. FALSE
Chapter 14
7. When the F test is used to test the overall significance of a multiple regression model, if the null hypothesis is rejected, it can be concluded that all of the independent variables X1, X2, (Xk are significantly related to the dependent variable Y.FALSE
8. An application of the multiple regression model generated the following results involving the F test of the overall regression model: p-value=.0012, R2=.67 and s=.076. Thus, the null hypothesis, which states that none of the independent variables are significantly related to the dependent variable, should be rejected even at the .01 level of significance.TRUE
9. High Multicollinearity problem occurs when the Independent variables are highly correlated with the Dependent variable. TRUE
10. The assumption of independent error terms in regression analysis is often violated when using time series data and is called the problem of Autocorrelation. TRUE
11. Homoscedasticity problem occurs when the assumption of constant error variance is violated. FALSE
Multiple Choices(Two points each)
Chapter 13
1. All of the following are assumptions of the error terms in the simple linear regression model except :
A. Errors are normally distributed
B. Error terms have a mean of zero
C. Error terms have a constant variance
D. Error terms depend on the explanatory variable
ANS- D
2. The point estimate of the variance in a regression model is
A. SSE
B. MSE
C. se
D. b1
ANS- B
3. The least squares regression line minimizes the sum of the
A. Sum of Differences between actual and predicted Y values
B. Sum of Squared differences between actual and predicted X values
C. Sum of Absolute deviations between actual and predicted X values
D. Sum of Absolute deviations between actual and predicted Y values
E. Sum of Squared differences between actual and predicted Y values
ANS-E
4. The ___________ the R2 and the __________ the s (standard error), the stronger the relationship between the dependent variable and the independent variable.
A. Higher, lower
B. Lower, higher
C. Lower, lower
D. Higher, higher
ANS-A
5. In simple bivariate regression analysis, if the correlation coefficient is a positive value, then
A. The Y intercept must also be a positive value.
B. The coefficient of determination can be either positive or negative, depending on the value of the slope.
C. The least squares regression equation could either have a positive or a negative slope.
D. The standard error of estimate can either have a positive or a negative value.
E. The slope of the regression line must also be positive.
ANS-E
6. A researcher wants to explore the relationship between the grades students receive on their Midterm test and their...