91影视

We need to find the linear model appropriate to describe the relationship between seed count and seed weight or not.

No, The scatterplot shows a strong curved pattern.

We need to graphs and computer output from a least-squares regression analysis on the transformed data are shown.

Its scatterplot shows a more linear pattern and its residual plot shows no visible pattern.

We need to find the seed weight if the seed count is$3700$.

On the scatterplot, we that the variable on the horizontal axis is "ln(count)" and the variable on the vertical axis is "ln(weight)", so the variable is " while the -variable is " . The general regression equation is then:

$\ln \left(weight\right)=a+b\ln \left(count\right)$

The constant is given in the row "Constant" and in the column "Coef" of the computer output of model $B$:

$a=15.491$

The slope is given in the row "ln(count)" and in the column "Coef" of the computer output of model B:

$b=鈭�1.5222$

Replacing with $15.491$and with $鈭�1.5222$in the general regression equation, we have:

$\ln \left(weight\right)=15.491鈭�1.5222\ln \left(count\right)$

Replace "count" by $3700$and evaluate:

$\ln \left(weight\right)=15.491鈭�1.5222\ln \left(3700\right)鈮�2.9845$

Take the exponential of each side:

$weight=e^{\ln weight}=e^{2.9845}鈮�19.7760$

Thus the predicted weight is$19.7760mg$.

We need to find the value of$r^2$for in model.

About $86.3\%$of the variation in $In$(seed weight) is accounted for by the linear modal relating $In$(seed weight ) to$In$(seed count.)