Answer Happy

Many different interest groups — such as the lumber
industry, ecologists, and foresters — benefit from being able to
predict the volume (in cubic feet) of a tree just by knowing its
diameter (in inches). Let's use a data set (Shortleaf 2.xlsx) of n
= 70 shortleaf pines to learn not only about the relationship
between the diameter and volume of shortleaf pines, but also about
the benefits of simultaneously transforming both the response
variable and the explanatory variable.
NOTE: Copy and paste the wordings (highlighted in
yellow) into the section below as is appropriate. Use
only the highlighted wordings. Do not add any extra space or
symbol when copying and pasting into the text box.
a) Make a scatterplot showing the diameter vs. volume.
Describe the association.
R2 = [round answer to 4 decimal
places. Please use a zero (0) before the decimal
point]
low
- high - not linear
- linear
Although the R2 is quite , the fitted
line plot suggests that the relationship between tree volume and
tree diameter is .
b) Make a scatterplot showing the logarithm (log10) of
diameter vs. volume. Describe the association.
diameter
- volume -
changed - did not
change
Transforming only the values the
non-linearity at all.
c) Make a scatterplot showing the logarithm (log10) of
diameter vs. logarithm (log10) of volume. Describe the
association.
Let's see if transforming both
the diameter and volume values does it for us. Wow!
The fitted line plot should give us hope!
R2 = [round answer to 4 decimal
places. Please use a zero (0) before the decimal
point]
non-linear and weak
- linear and strong
- linear and weak
The relationship between the log 10 of the diameter and the log 10
of the volume looks .
The regression equation is:
log⁡10(diameter)=^ − + ×log⁡10(volume) [round
answer to 4 decimal places.]