consider the multiple regression model shown next between the dependent variable
ID: 3049475 • Letter: C
Question
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:
4.02
3.83
2.53
2.61
2. The variance inflation factor can be used to reduce multicollinearity by ________.
Testing the null hypothesis that all regression coefficients equal zero
Decreasing homoscedasticity
Evaluating the distribution of residuals
Eliminating variables for a multiple regression model
3. Using the following information:
X = -12.8094 + 2.1794
= -12.80894 + 2.1794X
= 2.1794 - 12.8094X
12.8094 X = 2.1794
0.0, 4.05
6.842, 9.497
4.15, 12.25
2.67, 5.33
Here is the data for quesiton 3
4.02
3.83
2.53
2.61
2. The variance inflation factor can be used to reduce multicollinearity by ________.
Testing the null hypothesis that all regression coefficients equal zero
Decreasing homoscedasticity
Evaluating the distribution of residuals
Eliminating variables for a multiple regression model
3. Using the following information:
The regression equation is ________.
X = -12.8094 + 2.1794
= -12.80894 + 2.1794X
= 2.1794 - 12.8094X
12.8094 X = 2.1794
4. A regression analysis yields the following information:
; n = 10; syx = 1.66; X = 32; X2 = 134;
Compute the 95% confidence interval when X = 4.
0.0, 4.05
6.842, 9.497
4.15, 12.25
2.67, 5.33
Here is the data for quesiton 3
Explanation / Answer
Dear student please post the question one at a time
1)For k = 4 and n = 35, [n - (k + 1)] = 30. Using critical values of theF Distribution at the 1% level of significance,
for df numerator = 4 and df denomination = 30,
then the critical Fvalue is 4.02.
2) The variance inflation factor can be used to reduce multicollinearity by Eliminating variables for a multiple regression models
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