In: Statistics and Probability
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 |
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 | |||||
r² | 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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