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Regression and Forecastng (L) Question What does the R-squared measure for the following linear regression: Y-...
ek-tin Based on the following regression output, what proportion the total variation in Y is explained...
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Based on the following regression output, what proportion the total variation in Y is explained by X? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA di SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 Residual 8 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 0.917214 o b.9.385572...
What information does R (that is, r-squared) provide in general about the fit of a regression...
What information does R (that is, r-squared) provide in general about the fit of a regression model? It is exactly equal to the correlation between X and Y. It tells us the proportion of variability in the dependent variable, Y, that is explained by the model. It tells us the proportion of variability in the independent variable, X, that is explained by the model We should keep choosing different independent variables until R equals 1 O The closer R is...
In a simple linear regression analysis, the following sum of squares are produced: ∑(y−y¯)2=500 ∑(y−y′)2=100 ∑(y′−y¯)2=400...
In a simple linear regression analysis, the following sum of squares are produced: ∑(y−y¯)2=500 ∑(y−y′)2=100 ∑(y′−y¯)2=400 The proportion of the variation in Y that is explained by the variation in X is: a.) 80% b.) 20% c.) 50% d.) 25%
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...
Consider a multiple linear regression model Y; = Bo + B1Xi1 + B22:2 + 33213 +...
Consider a multiple linear regression model Y; = Bo + B1Xi1 + B22:2 + 33213 + Blog(x14) + Ej. We have the following statistics for the regression Call: 1m formula = y “ x1 + x2 + x3 + log(x4) Coefficients: Estimate Std. Error t value Pr(>1t|) (Intercept) 154.1928 194.9062 0.791 0.432938 x1 -4.2280 2.0301 -2.083 0.042873 * x2 -6.1353 2.1936 -2.797 0.007508 ** x3 0.4719 0.1285 3.672 0.000626 *** x4 26.7552 9.3374 2.865 0.006259 ** Signif. codes: O '***'...
Consider a multiple linear regression model Y; = Bo + B1Xi1 + B22:2 + 33213 +...
Consider a multiple linear regression model Y; = Bo + B1Xi1 + B22:2 + 33213 + Blog(x14) + Ej. We have the following statistics for the regression Call: 1m formula = y “ x1 + x2 + x3 + log(x4) Coefficients: Estimate Std. Error t value Pr(>1t|) (Intercept) 154.1928 194.9062 0.791 0.432938 x1 -4.2280 2.0301 -2.083 0.042873 * x2 -6.1353 2.1936 -2.797 0.007508 ** x3 0.4719 0.1285 3.672 0.000626 *** x4 26.7552 9.3374 2.865 0.006259 ** Signif. codes: O '***'...
QUESTION 1 Consider the following OLS regression line (or sample regression function): wage =-2.10+ 0.50 educ...
QUESTION 1 Consider the following OLS regression line (or sample regression function): wage =-2.10+ 0.50 educ (1), where wage is hourly wage, measured in dollars, and educ years of formal education. According to (1), a person with no education has a predicted hourly wage of [wagehat] dollars. (NOTE: Write your answer in number format, with 2 decimal places of precision level; do not write your answer as a fraction. Add a leading minus sign symbol, a leading zero and trailing...
х Run a regression analysis on the following bivariate set of data with y as the...
х Run a regression analysis on the following bivariate set of data with y as the response variable. y 28.2 50.9 26.9 60.8 19.2 46.9 23.1 28.6 28.7 69.3 30.4 58.1 40.6 77.3 25.6 60.3 23.1 22.5 23.1 46 19.2 37.2 34.2 74.1 Find the correlation coefficient and report it accurate to three decimal places. What proportion of the variation in y can be explained by the variation in the values of x? Report answer as a percentage accurate to...
Use the following linear regression equation to answer the questions. X1 = 1.7 + 3.6x2 -...
Use the following linear regression equation to answer the questions. X1 = 1.7 + 3.6x2 - 8.4x3 + 1.5x4 (a) Which variable is the response variable? O X1 O X2 O X4 O X3 Which variables are the explanatory variables? (Select all that apply.) X3 X1 U X2 (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant X2 coefficient X3 coefficient X4 coefficient (c) If x2 = 8, X3 = 5, and x4...
Part A Run a regression on the following dataset. What proportion of the variation in Y...
Part A Run a regression on the following dataset. What proportion of the variation in Y is explained by the regression? Also, what is the standard error of the estimate? X Y 262 14,041 319 16,953 361 18,984 381 19,870 405 20,953 439 22,538 472 23,985 508 25,641 547 27,365 592 29,967 a. 99.95%, 24,446.06 b. 99.95%; 0.5042 c. 99.91%; 195,568.50 d. 99.91%; 156.35 e. None of the above Part B Which of the following statements is correct? a. Based...
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Based on the following regression output, what proportion the total variation in Y is explained by X? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA di SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 Residual 8 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 0.917214 o b.9.385572...
What information does R (that is, r-squared) provide in general about the fit of a regression model? It is exactly equal to the correlation between X and Y. It tells us the proportion of variability in the dependent variable, Y, that is explained by the model. It tells us the proportion of variability in the independent variable, X, that is explained by the model We should keep choosing different independent variables until R equals 1 O The closer R is...
Consider a multiple linear regression model Y; = Bo + B1Xi1 + B22:2 + 33213 + Blog(x14) + Ej. We have the following statistics for the regression Call: 1m formula = y “ x1 + x2 + x3 + log(x4) Coefficients: Estimate Std. Error t value Pr(>1t|) (Intercept) 154.1928 194.9062 0.791 0.432938 x1 -4.2280 2.0301 -2.083 0.042873 * x2 -6.1353 2.1936 -2.797 0.007508 ** x3 0.4719 0.1285 3.672 0.000626 *** x4 26.7552 9.3374 2.865 0.006259 ** Signif. codes: O '***'...
Consider a multiple linear regression model Y; = Bo + B1Xi1 + B22:2 + 33213 + Blog(x14) + Ej. We have the following statistics for the regression Call: 1m formula = y “ x1 + x2 + x3 + log(x4) Coefficients: Estimate Std. Error t value Pr(>1t|) (Intercept) 154.1928 194.9062 0.791 0.432938 x1 -4.2280 2.0301 -2.083 0.042873 * x2 -6.1353 2.1936 -2.797 0.007508 ** x3 0.4719 0.1285 3.672 0.000626 *** x4 26.7552 9.3374 2.865 0.006259 ** Signif. codes: O '***'...
QUESTION 1 Consider the following OLS regression line (or sample regression function): wage =-2.10+ 0.50 educ (1), where wage is hourly wage, measured in dollars, and educ years of formal education. According to (1), a person with no education has a predicted hourly wage of [wagehat] dollars. (NOTE: Write your answer in number format, with 2 decimal places of precision level; do not write your answer as a fraction. Add a leading minus sign symbol, a leading zero and trailing...
х Run a regression analysis on the following bivariate set of data with y as the response variable. y 28.2 50.9 26.9 60.8 19.2 46.9 23.1 28.6 28.7 69.3 30.4 58.1 40.6 77.3 25.6 60.3 23.1 22.5 23.1 46 19.2 37.2 34.2 74.1 Find the correlation coefficient and report it accurate to three decimal places. What proportion of the variation in y can be explained by the variation in the values of x? Report answer as a percentage accurate to...
Use the following linear regression equation to answer the questions. X1 = 1.7 + 3.6x2 - 8.4x3 + 1.5x4 (a) Which variable is the response variable? O X1 O X2 O X4 O X3 Which variables are the explanatory variables? (Select all that apply.) X3 X1 U X2 (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant X2 coefficient X3 coefficient X4 coefficient (c) If x2 = 8, X3 = 5, and x4...
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