Statistics: Informed Decisions Using Data (4th Edition)

Published by Pearson
ISBN 10: 0321757270
ISBN 13: 978-0-32175-727-2

Chapter 14 - Section 14.3 - Assess Your Understanding - Vocabulary and Skill Building - Page 721: 14c

Answer

After removing, in this order, $x_2$, $x_4$ and $x_3$: $ŷ=200.0- 1.624x_1$

Work Step by Step

Let's remove $x_2$ (see previous item) In MINITAB, enter the $x_1$ values in C1, the $x_3$ values in C3, the $x_4$ values in C4 and the $y$ values in C5. Select Stats -> Regression -> Regression -> Fit Regression Model Enter C5 in "Responses" and C1 C3 C4 in "Continuous Predictors" The least-squares regression line will be shown in "Regression Equation", where C5 is $ŷ$, C1 is $x_1$, C3 is $x_3$ and C4 is $x_4$ $ŷ=154.7-1.255x_1+3.43 x_3+0.105x_4$ $H_0: β_1=β_3=β_4=0$ versus $H_1: at~least~one~β_i\ne0$ $F_0=7.60$ with a P-value $=0.010\ltα$. Reject the null hypothesis. The model is significant. 1) $H_0: β_1=0$ versus $H_1: β_1\ne0$ $t_0=-2.58$ with a P-value $=0.032\ltα$. Reject the null hypothesis. 3) $H_0: β_3=0$ versus $H_1: β_3\ne0$ $t_0=1.64$ with a P-value $=0.140\gtα$. Do not reject the null hypothesis. 4) $H_0: β_4=0$ versus $H_1: β_4\ne0$ $t_0=0.20$ with a P-value $=0.844\gtα$. Do not reject the null hypothesis. Now, let's remove $x_4$ (the highest P-value): Select Stats -> Regression -> Regression -> Fit Regression Model Enter C5 in "Responses" and C1 C3 in "Continuous Predictors" The least-squares regression line will be shown in "Regression Equation", where C5 is $ŷ$, C1 is $x_1$ and C3 is $x_3$ $ŷ=164.9-1.308 x_1+3.34x_3$ $H_0: β_1=β_3=0$ versus $H_1: at~least~one~β_i\ne0$ $F_0=12.73$ with a P-value $=0.002\ltα$. Reject the null hypothesis. The model is significant. 1) $H_0: β_1=0$ versus $H_1: β_1\ne0$ $t_0=-3.37$ with a P-value $=0.008\ltα$. Reject the null hypothesis. 3) $H_0: β_3=0$ versus $H_1: β_3\ne0$ $t_0=1.73$ with a P-value $=0.118\gtα$. Do not reject the null hypothesis. Now, let's remove $x_3$: Select Stats -> Regression -> Regression -> Fit Regression Model Enter C5 in "Responses" and C1 in "Continuous Predictors" The least-squares regression line will be shown in "Regression Equation", where C5 is $ŷ$ and C1 is $x_1$ $ŷ=200.0- 1.624x_1$ 1) $H_0: β_1=0$ versus $H_1: β_1\ne0$ $t_0=-4.33$ with a P-value $=0.001\ltα$. Reject the null hypothesis.
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