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(b) Use the below output to test the null hypothesis Ho: Bx -0.50w = -0.5 against the two tailed alternative H₁ Bx - 0.56w -0.5 at a 1% significance level. Be sure to explain how you have been able to make use of the output given. Note the variable Wplushalf X = W +0.5X Call: 1m (formula = Y X + 2 + WplushalfX) Residuals: 1Q Median 30 Max -1.8984 -0.4832 0.2532 0.5756 2.0092 Min Coefficients: Estimate Std. Error t value Pr (>It|) 4.67189 1.66765 2.801 -0.63364 0.39078 -1.621 -2.51074 0.04934 -50.885 WplushalfX 11.01191 0.01805 609.985 (Intercept) X Z --- 0.0099 ** 0.1180 <2e-16 *** <20-16 *** Signif. codes: 0 **** 0.001 ** 0.01 0.05 0.1¹1 Residual standard error: 1.016 on 24 degrees of freedom Multiple R-squared: 0.9999, Adjusted R-squared: 0.9999 F-statistic: 1.309e+05 on 3 and 24 DF, p-value: < 2.2e-16

(b) Use the below output to test the null hypothesis Ho: Bx -0.50w = -0.5 against the two tailed alternative H₁ Bx - 0.56w -0.5 at a 1% significance level. Be sure to explain how you have been able to make use of the output given. Note the variable Wplushalf X = W +0.5X Call: 1m (formula = Y X + 2 + WplushalfX) Residuals: 1Q Median 30 Max -1.8984 -0.4832 0.2532 0.5756 2.0092 Min Coefficients: Estimate Std. Error t value Pr (>It|) 4.67189 1.66765 2.801 -0.63364 0.39078 -1.621 -2.51074 0.04934 -50.885 WplushalfX 11.01191 0.01805 609.985 (Intercept) X Z --- 0.0099 ** 0.1180 <2e-16 *** <20-16 *** Signif. codes: 0 **** 0.001 ** 0.01 0.05 0.1¹1 Residual standard error: 1.016 on 24 degrees of freedom Multiple R-squared: 0.9999, Adjusted R-squared: 0.9999 F-statistic: 1.309e+05 on 3 and 24 DF, p-value: < 2.2e-16

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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(b) Use the below output to test the null hypothesis Ho: Bx -0.50w = -0.5 against the two tailed alternative H₁: Bx - 0.56w -0.5 at a 1% significance level. Be sure to explain how you have been able to make use of the output given. Note the variable Wplushalf X = W +0.5X Call: 1m (formula = Y ¯ X + Z + WplushalfX) Residuals: Min 10 Median 30 -1.8984 -0.4832 0.2532 0.5756 2.0092 Coefficients: (Intercept) 4.67189 -0.63364 Z -2.51074 WplushalfX 11.01191 Max Estimate Std. Error t value --- 1.66765 2.801 0.39078 -1.621 0.04934 -50.885 0.01805 609.985 Pr (>ltl) 0.0099 ** 0.1180 <2e-16 *** <20-16 *** Signif. codes: 0 *** 0.001 ** 0.01 0.05. 0.1 C Residual standard error: 1.016 on 24 degrees of freedom Multiple R-squared: 0.9999, Adjusted R-squared: 0.9999 F-statistic: 1.309e+05 on 3 and 24 DF, p-value: < 2.2e-16 1
Transcribed Image Text:(b) Use the below output to test the null hypothesis Ho: Bx -0.50w = -0.5 against the two tailed alternative H₁: Bx - 0.56w -0.5 at a 1% significance level. Be sure to explain how you have been able to make use of the output given. Note the variable Wplushalf X = W +0.5X Call: 1m (formula = Y ¯ X + Z + WplushalfX) Residuals: Min 10 Median 30 -1.8984 -0.4832 0.2532 0.5756 2.0092 Coefficients: (Intercept) 4.67189 -0.63364 Z -2.51074 WplushalfX 11.01191 Max Estimate Std. Error t value --- 1.66765 2.801 0.39078 -1.621 0.04934 -50.885 0.01805 609.985 Pr (>ltl) 0.0099 ** 0.1180 <2e-16 *** <20-16 *** Signif. codes: 0 *** 0.001 ** 0.01 0.05. 0.1 C Residual standard error: 1.016 on 24 degrees of freedom Multiple R-squared: 0.9999, Adjusted R-squared: 0.9999 F-statistic: 1.309e+05 on 3 and 24 DF, p-value: < 2.2e-16 1
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