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Answer the questions based on the regression results summarized below (if necessary, scroll down or right to view the (a) The regression is overall not significant ata =0.01 significance level. entire table). O True OLS Regression Resulta O False www * Dep. Variabler VariableY OLS Least Squares Tue, 25 May 2021 R-squared: Adj. R-squared F-statistic: 0.608 0.605 Model Method: (b) The independent variables can collectively explain % of the variability in Variable Y. (Round to one decimal place, 222.9 2.37e-87 Dates Prob (P-statistie) Log-Likelihood including any zeros.) Time No. Obeervatione DE Residuals Df Hodel. O1619 -1284.6 2577. 436 432 AIC DICI (c) There is a significant relation between the dependent variable and gach of the three independent variables ata = 0.01 significance level. 2593. Covariance Type: nonrobuat td e O True coet (0.025 0.9751 O False 25.941 -17.056 53.737 -0.713 Intercept Variable R Variable z VariableO 49.9519 -0.8064 1.926 0.047 0.000 0.000 46.167 199 0.0104 -1.0051 -0.009 -1.217 0.010 1.036 0.301 0.000 0.030 -0.793 (d) If Variable Q increases one unit, Variable Y would 0.108 -9.330 Omnibun Prob(Omnibus) s0.296 0.000 Durbin-wataon Jarque-Bera (JB) O A. Increase units 1.174 148.594 Skev Kurtosis Prob( JB) 1.038 : 5.41e-33 Cond. No. OB. Decrease units 4.967 644. OC. Not change (Round to three decimal places, including any zeros.) (e) Regression residuals are Normally distributed a = 0.01 significance level and therefore satisfy linear regression Normality assumption. O True O False

Answer the questions based on the regression results summarized below (if necessary, scroll down or right to view the (a) The regression is overall not significant ata =0.01 significance level. entire table). O True OLS Regression Resulta O False www * Dep. Variabler VariableY OLS Least Squares Tue, 25 May 2021 R-squared: Adj. R-squared F-statistic: 0.608 0.605 Model Method: (b) The independent variables can collectively explain % of the variability in Variable Y. (Round to one decimal place, 222.9 2.37e-87 Dates Prob (P-statistie) Log-Likelihood including any zeros.) Time No. Obeervatione DE Residuals Df Hodel. O1619 -1284.6 2577. 436 432 AIC DICI (c) There is a significant relation between the dependent variable and gach of the three independent variables ata = 0.01 significance level. 2593. Covariance Type: nonrobuat td e O True coet (0.025 0.9751 O False 25.941 -17.056 53.737 -0.713 Intercept Variable R Variable z VariableO 49.9519 -0.8064 1.926 0.047 0.000 0.000 46.167 199 0.0104 -1.0051 -0.009 -1.217 0.010 1.036 0.301 0.000 0.030 -0.793 (d) If Variable Q increases one unit, Variable Y would 0.108 -9.330 Omnibun Prob(Omnibus) s0.296 0.000 Durbin-wataon Jarque-Bera (JB) O A. Increase units 1.174 148.594 Skev Kurtosis Prob( JB) 1.038 : 5.41e-33 Cond. No. OB. Decrease units 4.967 644. OC. Not change (Round to three decimal places, including any zeros.) (e) Regression residuals are Normally distributed a = 0.01 significance level and therefore satisfy linear regression Normality assumption. O True O False

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Answer the questions based on the regression results summarized below (if necessary, scroll down or right to view the entire table). (a) The regression is overall not significant at c = 0.01 significance level. True OLS Regression Resulta O False ----- Dep. variable: Modeli Variable_Y R-squaredi Adj. R-squaredi F-statistic: Prob (P-statistic)) : Log-Likelihood: 0.608 OLS 0.605 (b) The independent variables can collectively explain % of the variability in Variable Y. (Round to one decimal place, Method: Least Squares Tue, 25 May 2021 08:16:19 222.9 Date: 2.37e-87 including any zeros.) Time: No. Obeervations: Df Residuals: -1284.6 436 AIC: 2577. (c) There is a significant relation between the dependent variable and each of the three independent variables at a = 0.01 significance level. 432 BIC: 2593. Df Model: 3 Covariance Type: noarobuat P>t| O True coef std err ro.025 0.9751 25.941 O False Intercept Variable_R Variable_z Variable_Q - 49.9519 1.926 0.000 46.167 53.737 -0.8064 0.0104 0.047 -17.056 0.000 -0.899 -0.713 0.010 1.036 0.301 -0.009 0.030 (d) If Variable Q increases one unit, Variable Y would -1.0051 0.108 -9.330 0-009 0.000 -1.217 -0.793 O A. Increase Durbin-Watson: Jarque-Bera (JB) : Prob(JB) Cond. No. ----- Omnibus: 80.296 1.174 units 0.000 Prob(Omnibus): Skew: 148.594 1.038 5.4le-33 O B. Decrease units Kurtosis: 4.967 644. - OC. Not change (Round to three decimal places, including any zeros.) (e) Regression residuals are Normally distributed a = 0.01 significance level and therefore satisfy linear regression Normality assumption. True False
Transcribed Image Text:Answer the questions based on the regression results summarized below (if necessary, scroll down or right to view the entire table). (a) The regression is overall not significant at c = 0.01 significance level. True OLS Regression Resulta O False ----- Dep. variable: Modeli Variable_Y R-squaredi Adj. R-squaredi F-statistic: Prob (P-statistic)) : Log-Likelihood: 0.608 OLS 0.605 (b) The independent variables can collectively explain % of the variability in Variable Y. (Round to one decimal place, Method: Least Squares Tue, 25 May 2021 08:16:19 222.9 Date: 2.37e-87 including any zeros.) Time: No. Obeervations: Df Residuals: -1284.6 436 AIC: 2577. (c) There is a significant relation between the dependent variable and each of the three independent variables at a = 0.01 significance level. 432 BIC: 2593. Df Model: 3 Covariance Type: noarobuat P>t| O True coef std err ro.025 0.9751 25.941 O False Intercept Variable_R Variable_z Variable_Q - 49.9519 1.926 0.000 46.167 53.737 -0.8064 0.0104 0.047 -17.056 0.000 -0.899 -0.713 0.010 1.036 0.301 -0.009 0.030 (d) If Variable Q increases one unit, Variable Y would -1.0051 0.108 -9.330 0-009 0.000 -1.217 -0.793 O A. Increase Durbin-Watson: Jarque-Bera (JB) : Prob(JB) Cond. No. ----- Omnibus: 80.296 1.174 units 0.000 Prob(Omnibus): Skew: 148.594 1.038 5.4le-33 O B. Decrease units Kurtosis: 4.967 644. - OC. Not change (Round to three decimal places, including any zeros.) (e) Regression residuals are Normally distributed a = 0.01 significance level and therefore satisfy linear regression Normality assumption. True False
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