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Yi= a + Bxi +€₁. Given a random sample of n = 25 observations, we have: Where Σy = 2597.51, Σ * = 598, Σ. - 7)2 = 5299.84, i=1 i=1 Σ(x-7)(y-7)=21618.64, e-6375.64, α. i=1 X ê₁ = yi - ĝi. 1. Estimate by the method of least squares the coefficients of the linear regression model 2. Conduct a test at the 5% significance level for the null hypothesis Ho: B= 0 versus the alternative H1: B*0 3. Running a second regression on a sample of n = 30 statistical units yields the results shown in the table below. i=1 Coefficients: Estimate Std. Error t value Pr (>1t|) (Intercept) 2.3058 0.451 0.655 4.0739 <2e-16 0.1622 Appropriately completing the above table, construct a 99% confdence interval for the coefficient

Yi= a + Bxi +€₁. Given a random sample of n = 25 observations, we have: Where Σy = 2597.51, Σ * = 598, Σ. - 7)2 = 5299.84, i=1 i=1 Σ(x-7)(y-7)=21618.64, e-6375.64, α. i=1 X ê₁ = yi - ĝi. 1. Estimate by the method of least squares the coefficients of the linear regression model 2. Conduct a test at the 5% significance level for the null hypothesis Ho: B= 0 versus the alternative H1: B*0 3. Running a second regression on a sample of n = 30 statistical units yields the results shown in the table below. i=1 Coefficients: Estimate Std. Error t value Pr (>1t|) (Intercept) 2.3058 0.451 0.655 4.0739 <2e-16 0.1622 Appropriately completing the above table, construct a 99% confdence interval for the coefficient

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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Assume the following relationship exists: Given a random sample of n = 25 observations, we have: Where Σy = 2597.51, Στ. = 598, Σπ. - π) = 5299.84, i=1 i=1 α. Yi= a + Bxi +€₁. êi = yi - Yi. X Σ(mi - Ξ)(y - 7) – 21618.64, = i=1 1. Estimate by the method of least squares the coefficients of the linear regression model 2. Conduct a test at the 5% significance level for the null hypothesis Ho: B= 0 versus the alternative H1: B=0 Coefficients: (Intercept) 3. Running a second regression on a sample of n = 30 statistical units yields the results shown in the table below. n Σ ε = 6375.64, 2.3058 4.0739 Estimate Std. Error t value Pr (>1t|) 0.451 0.655 <2e-16 0.1622 Appropriately completing the above table, construct a 99% confdence interval for the coefficient 4. Demonstrate how to obtain R² by appropriately decomposing the total deviance of yi
Transcribed Image Text:Assume the following relationship exists: Given a random sample of n = 25 observations, we have: Where Σy = 2597.51, Στ. = 598, Σπ. - π) = 5299.84, i=1 i=1 α. Yi= a + Bxi +€₁. êi = yi - Yi. X Σ(mi - Ξ)(y - 7) – 21618.64, = i=1 1. Estimate by the method of least squares the coefficients of the linear regression model 2. Conduct a test at the 5% significance level for the null hypothesis Ho: B= 0 versus the alternative H1: B=0 Coefficients: (Intercept) 3. Running a second regression on a sample of n = 30 statistical units yields the results shown in the table below. n Σ ε = 6375.64, 2.3058 4.0739 Estimate Std. Error t value Pr (>1t|) 0.451 0.655 <2e-16 0.1622 Appropriately completing the above table, construct a 99% confdence interval for the coefficient 4. Demonstrate how to obtain R² by appropriately decomposing the total deviance of yi
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