Homework Answers
Answer:-
19)
when a value is plugged in for x in a regression equation,the output value calculated y (y-prime) is known as a(n)
d.point estimate
20)
The cause and effect relationship of an input variable to an output variable ,may be that the output variable is also affected by an unknown second input variable called a
d.dependent variable.
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QUESTION 18 When a value is plugged in for x in a regression equation, the output...
18 QueSLIVIT TO Based on the following regression output, what is the equation of the regression...
18
QueSLIVIT TO Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.99313 0.98630 R Square Adjusted R Square Standard Error 0.98238 2.94802 10 Observations ANOVA df SS MS Significance F Regression 4379.182 2189.591 251.943 0.0000 Residual 7 60.836 8.691 9 Total 4440.017 Coefficients Standard Error t Stat P-value Lower 95% 14.169 3.856 3.674 Intercept 0.008 5.050 X Variable 1 0.985 0.114 8.607 0.000 0.714 X Variable 0.995 0.057 17.498 0.000...
1. In regression analysis, the Sum of Squares Total (SST) is a. The total variation of...
1. In regression analysis, the Sum of Squares Total (SST) is a. The total variation of the dependent variable b. The total variation of the independent variable c. The variation of the dependent variable that is explained by the regression line d. The variation of the dependent variable that is unexplained by the regression line Question 2 In regression analysis, the Sum of Squares Regression (SSR) is A. The total variation of the dependent variable B. The total variation of the independent variable...
QUESTION 1 If a t-test is performed in the context of a multiple regression model and...
QUESTION 1 If a t-test is performed in the context of a multiple regression model and the null hypothesis cannot be rejected, this means that A. the independent variable for which the test has been performed has a significant relationship with the dependent variable. B. the independent variable for which the test has been performed has no significant relationship with the dependent variable. C. all independent variables have a significant relationship with the dependent variable. D. no independent variable has...
For the following question (#19 and #20), please use the following multiple regression output. The dependent...
For the following question (#19 and #20), please use the following multiple regression output. The dependent variable is Home Price: ($) the independent variables are Number of Bedrooms, Size (square footage), and Pool (0 = no pool, 1 = pool). 19: Which statement is correct? SUMMARY OUTPUT A: The R square of 571 is the best goodness of fit statistic to use for multiple regression analyses. B: The Number of Bedrooms is not a significant predictor variable. Regression Statistics Multiple...
The β 1 term indicates a. the Y value for a given value of X. b....
The β 1 term indicates a. the Y value for a given value of X. b. the average change in Y for a unit change in X. c. the Y value when X equals zero. d. the change in observed X for a given change in Y. What does regression analysis attempt to establish? a. linearity in the relationship between independent variables b. a mathematical relationship between a dependent variable, for which future values will be forecast, and one or...
For the following questions (17-18), use the following regression output. The dependent variable is Assessed Value...
For the following questions (17-18), use the following regression output. The dependent variable is Assessed Value (5) and the independent variable is Floor Space (square feet) SUMMARY OUTPUT Regression Statistics Multiple 0.0084 R Square 0.9377 Adjusted R Square 00350 Standard Emor 116 5093 Observations 32 ANOVA Significance F 1.23E-19 Regression Residual Total 1 30 31 SS MS F 8035351.603 6036862 451.6772 4008959721 13303.2 6438747.875 Coefficients 16267 0.3087 Intercept Floor space Standard Error 5428 0.010 Star Rvale 2.980 0.006686 21 253...
33. Based on the regression In Y, =a+ß, In X, , where Y is the quantity...
33. Based on the regression In Y, =a+ß, In X, , where Y is the quantity of beef and X is beef price, and "In" stands for natural logarithm, we obtain the following regression output based on 100 observations: Dependent Variable: In Y Variable Intercept In X Parameter Estimate (a) ? -0.20 Standard Error t-value 2.175 1.300 0.0341 -5.865 r?: 0.258 What are the degrees of freedom in this model? a. 100. b. 2. c. 99. d. 98. e. Cannot...
Question 4 1.5 pts Which of the following statement is true based on the following regression...
Question 4 1.5 pts Which of the following statement is true based on the following regression equation? IQ = 4.0 + Reading Label * 5.6 A unit point change in IQ will result in 5.6-point increase in reading label. O A unit point change in IQ will result in 9.6-point increase in reading label. A unit point change in reading label will increase IQ by 5.6 point Reading label is not a good predictor of IQ. Question 5 1.5 pts...
) Interpret the value of the slope (rounded to two decimal places) in the regression equation...
) Interpret the value of the slope (rounded to two decimal places) in the regression equation found in part 1c in the context of the question, using a complete sentence. 1f) State and interpret the value of the coefficient of determination (R-sq expressed as a percentage) found in part 1c in the context of the question in a complete sentence. 1g) Use the regression equation (with both intercept and slope rounded to two decimal places) to predict the final selling...
18
QueSLIVIT TO Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.99313 0.98630 R Square Adjusted R Square Standard Error 0.98238 2.94802 10 Observations ANOVA df SS MS Significance F Regression 4379.182 2189.591 251.943 0.0000 Residual 7 60.836 8.691 9 Total 4440.017 Coefficients Standard Error t Stat P-value Lower 95% 14.169 3.856 3.674 Intercept 0.008 5.050 X Variable 1 0.985 0.114 8.607 0.000 0.714 X Variable 0.995 0.057 17.498 0.000...
QUESTION 1 If a t-test is performed in the context of a multiple regression model and the null hypothesis cannot be rejected, this means that A. the independent variable for which the test has been performed has a significant relationship with the dependent variable. B. the independent variable for which the test has been performed has no significant relationship with the dependent variable. C. all independent variables have a significant relationship with the dependent variable. D. no independent variable has...
For the following question (#19 and #20), please use the following multiple regression output. The dependent variable is Home Price: ($) the independent variables are Number of Bedrooms, Size (square footage), and Pool (0 = no pool, 1 = pool). 19: Which statement is correct? SUMMARY OUTPUT A: The R square of 571 is the best goodness of fit statistic to use for multiple regression analyses. B: The Number of Bedrooms is not a significant predictor variable. Regression Statistics Multiple...
For the following questions (17-18), use the following regression output. The dependent variable is Assessed Value (5) and the independent variable is Floor Space (square feet) SUMMARY OUTPUT Regression Statistics Multiple 0.0084 R Square 0.9377 Adjusted R Square 00350 Standard Emor 116 5093 Observations 32 ANOVA Significance F 1.23E-19 Regression Residual Total 1 30 31 SS MS F 8035351.603 6036862 451.6772 4008959721 13303.2 6438747.875 Coefficients 16267 0.3087 Intercept Floor space Standard Error 5428 0.010 Star Rvale 2.980 0.006686 21 253...
33. Based on the regression In Y, =a+ß, In X, , where Y is the quantity of beef and X is beef price, and "In" stands for natural logarithm, we obtain the following regression output based on 100 observations: Dependent Variable: In Y Variable Intercept In X Parameter Estimate (a) ? -0.20 Standard Error t-value 2.175 1.300 0.0341 -5.865 r?: 0.258 What are the degrees of freedom in this model? a. 100. b. 2. c. 99. d. 98. e. Cannot...
Question 4 1.5 pts Which of the following statement is true based on the following regression equation? IQ = 4.0 + Reading Label * 5.6 A unit point change in IQ will result in 5.6-point increase in reading label. O A unit point change in IQ will result in 9.6-point increase in reading label. A unit point change in reading label will increase IQ by 5.6 point Reading label is not a good predictor of IQ. Question 5 1.5 pts...
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