2. Test the significance of explanatory variable. (a) There is no evidence that the explanatory variable is significant (p-value > 0.1) (b) There is some evidence that the explanatory variable is significant (0.05 ≤ p-value < 0.1) I (c) There is strong evidence that the explanatory variable is signifi- cant (0.01 ≤ p-value < 0.05) (d) There is very strong evidence that the explanatory variable is significant (0.001 ≤ p-value < 0.01)

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
Section: Chapter Questions
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Please solve both of the attached subparts of the problem. They are all from one question that is above question 1. Refer to that part for data. Thanks!

2. Test the significance of explanatory variable.
(a) There is no evidence that the explanatory variable is significant
(p-value 20.1)
(b) There is some evidence that the explanatory variable is significant
(0.05 ≤ p-value < 0.1)
I
(c) There is strong evidence that the explanatory variable is signifi-
cant
(0.01 ≤ p-value < 0.05)
(d) There is very strong evidence that the explanatory variable is
significant
(0.001 ≤ p-value < 0.01)
Transcribed Image Text:2. Test the significance of explanatory variable. (a) There is no evidence that the explanatory variable is significant (p-value 20.1) (b) There is some evidence that the explanatory variable is significant (0.05 ≤ p-value < 0.1) I (c) There is strong evidence that the explanatory variable is signifi- cant (0.01 ≤ p-value < 0.05) (d) There is very strong evidence that the explanatory variable is significant (0.001 ≤ p-value < 0.01)
Since elderly people may have difficulty standing straight, a study aims to
predict overall height from height to the knee. Here are data (in centimeters,
cm) for five elderly men.
55.2
43.5 44.8
192.1 153.3 146.4 162.7 169.1
Knee Height (cm) 57.7 47.4
Overall Height (cm) 192.1
Let's assume a regression model
Overall height = Bo + B₁ x Knee height + e
1. Which R command should you use to fit the model if you have defined
variables as
I
knee = c(57.7, 47.4, 43.5, 44.8, 55.2)
overall = c(192.1, 153.3, 146.4, 162.7, 169.1)
Transcribed Image Text:Since elderly people may have difficulty standing straight, a study aims to predict overall height from height to the knee. Here are data (in centimeters, cm) for five elderly men. 55.2 43.5 44.8 192.1 153.3 146.4 162.7 169.1 Knee Height (cm) 57.7 47.4 Overall Height (cm) 192.1 Let's assume a regression model Overall height = Bo + B₁ x Knee height + e 1. Which R command should you use to fit the model if you have defined variables as I knee = c(57.7, 47.4, 43.5, 44.8, 55.2) overall = c(192.1, 153.3, 146.4, 162.7, 169.1)
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