In: Math
Smitley and Davis studied the changes in gypsy moth egg mass density over one generation as a function of the initial egg mass density in a control plot and two treated plots. The data below are for the control plot.
| Initial Egg Mass (per 0.04 ha) | 50 | 75 | 100 | 160 | 175 | 180 | 200 | 
| Change in Egg Mass Density (%) | 250 | -100 | -25 | -25 | -50 | 50 | 0 | 
A. On the basis of the data given in the table, find the
best-fitting logarithmic function using least squares. State the
square of the correlation coefficient. (Note that the authors used
logarithms to the base 10.) (Use 4 decimal places in your
answers.)
y(x) =
r2 =
B. Use this model to estimate the change in egg mass density with
an initial egg mass of 120 per 0.04 ha. (Use 4 decimal places in
your answer.)
With an initial egg mass of 120 per 0.04ha, the change in mass
density is
%
Smitley and Davis studied the changes in gypsy moth egg mass density over one generation as a function of the initial egg mass density in a control plot and two treated plots. The data below are for the control plot.
| 
 Initial Egg Mass (per 0.04 ha)  | 
 50  | 
 75  | 
 100  | 
 160  | 
 175  | 
 180  | 
 200  | 
| 
 Change in Egg Mass Density (%)  | 
 250  | 
 -100  | 
 -25  | 
 -25  | 
 -50  | 
 50  | 
 0  | 
A. On the basis of the data given in the table, find the
best-fitting logarithmic function using least squares. State the
square of the correlation coefficient. (Note that the authors used
logarithms to the base 10.) (Use 4 decimal places in your
answers.)
y(x) =513.2945-239.6202 *log10(x)
r2
=0.2340
B. Use this model to estimate the change in egg mass density with
an initial egg mass of 120 per 0.04 ha. (Use 4 decimal places in
your answer.)
With an initial egg mass of 120 per 0.04ha, the change in mass
density is
15.0807%
| 
 Regression Analysis  | 
||||||
| 
 r²  | 
 0.2340  | 
 n  | 
 7  | 
|||
| 
 r  | 
 -0.4837  | 
 k  | 
 1  | 
|||
| 
 Std. Error  | 
 108.838  | 
 Dep. Var.  | 
 Change in Egg Mass Density (%)  | 
|||
| 
 ANOVA table  | 
||||||
| 
 Source  | 
 SS  | 
 df  | 
 MS  | 
 F  | 
 p-value  | 
|
| 
 Regression  | 
 18,092.4716  | 
 1  | 
 18,092.4716  | 
 1.53  | 
 .2714  | 
|
| 
 Residual  | 
 59,228.9570  | 
 5  | 
 11,845.7914  | 
|||
| 
 Total  | 
 77,321.4286  | 
 6  | 
||||
| 
 Regression output  | 
 confidence interval  | 
|||||
| 
 variables  | 
 coefficients  | 
 std. error  | 
 t (df=5)  | 
 p-value  | 
 95% lower  | 
 95% upper  | 
| 
 Intercept  | 
 513.2945  | 
 405.8668  | 
 1.265  | 
 .2617  | 
 -530.0195  | 
 1,556.6085  | 
| 
 Log10(Initial Egg Mass (per 0.04 ha))  | 
 -239.6202  | 
 193.8905  | 
 -1.236  | 
 .2714  | 
 -738.0316  | 
 258.7912  | 
when x=120,
y(120) =513.2945-239.6202 *log10(120) =15.080674