Question

In: Statistics and Probability

Measuring the height of a California redwood tree is very difficult because these trees grow to...

Measuring the height of a California redwood tree is very
difficult because these trees grow to heights of over 300 feet. People
familiar with these trees understand that the height of a California
redwood tree is related to other characteristics of the tree,
including the diameter of the tree at the breast height of a person.
The data in Redwood represent the height (in feet) and diameter
(in inches) at the breast height of a person for a sample of 21 California
redwood trees.
a. Assuming a linear relationship, use the least-squares method
to compute the regression coefficients b0 and b1. State the regression
equation that predicts the height of a tree based on the
tree’s diameter at breast height of a person.
b. Interpret the meaning of the slope in this equation.
c. Predict the mean height for a tree that has a breast height diameter
of 25 inches.
d. Interpret the meaning of the coefficient of determination in this
problem.
e. Perform a residual analysis on the results and determine the adequacy
of the model.

Data Is Below:

Height Diameter at breast height Bark thickness
122.0 20 1.1
193.5 36 2.8
166.5 18 2.0
82.0 10 1.2
133.5 21 2.0
156.0 29 1.4
172.5 51 1.8
81.0 11 1.1
148.0 26 2.5
113.0 12 1.5
84.0 13 1.4
164.0 40 2.3
203.3 52 2.0
174.0 30 2.5
159.0 22 3.0
205.0 42 2.6
223.5 45 4.3
195.0 54 4.0
232.5 39 2.2
190.5 36 3.5
100.0 8 1.4

Solutions

Expert Solution

a. Assuming a linear relationship, use the least-squares method
to compute the regression coefficients b0 and b1. State the regression
equation that predicts the height of a tree based on the
tree’s diameter at breast height of a person.

The regression equation is:

Height = 78.7911 + 2.6735*diameter at breast height
b. Interpret the meaning of the slope in this equation.

For every diameter at breast height, height of a tree increases by 2.6735.
c. Predict the mean height for a tree that has a breast height diameter
of 25 inches.

Height = 145.6280
d. Interpret the meaning of the coefficient of determination in this
problem.

72.9% of the variation in the model is explained.
e. Perform a residual analysis on the results and determine the adequacy
of the model.

The residual plot is:

The model is adequate.

Height Diameter at breast height
122 20
193.5 36
166.5 18
82 10
133.5 21
156 29
172.5 51
81 11
148 26
113 12
84 13
164 40
203.3 52
174 30
159 22
205 42
223.5 45
195 54
232.5 39
190.5 36
100 8
0.729
r   0.854
Std. Error   24.747
n   21
k   1
Dep. Var. Height
ANOVA table
Source SS   df   MS F p-value
Regression 31,279.339 1   31,279.339 51.08 8.58E-07
Residual 11,635.946 19   612.4182
Total 42,915.286 20  
Regression output confidence interval
variables coefficients std. error    t (df=19) p-value 95% lower 95% upper
Intercept 78.7911
Diameter at breast height 2.6735 0.3741 7.147 8.58E-07 1.8905 3.4564
Observation Height Predicted Residual
1 122.00 132.26 -10.26
2 193.50 175.04 18.46
3 166.50 126.91 39.59
4 82.00 105.53 -23.53
5 133.50 134.93 -1.43
6 156.00 156.32 -0.32
7 172.50 215.14 -42.64
8 81.00 108.20 -27.20
9 148.00 148.30 -0.30
10 113.00 110.87 2.13
11 84.00 113.55 -29.55
12 164.00 185.73 -21.73
13 203.30 217.81 -14.51
14 174.00 159.00 15.00
15

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