inches.

What would se be for the least-squares line used to predict 18-year-old height from 6-year-old height?

d. Referring to Part (c), suppose that you wanted to predict the past value of 6-year-old height from knowledge of 18-year-old height. Find the equation for the appropriate least-squares line. What is the corresponding value of se? y^ 5 5.5 described a study of the effectiveness of pomegranate fruit extract (PFE) in slowing the growth of prostate cancer tumors (Proceedings of the National Academy of Sciences [October 11, 2005]:

14813–14818]. Figure 5.11 from that example is reproduced here. Based on this figure, we noted that for the

.2% PFE group, the relationship between average tumor volume and number of days after injection of cancer cells appears curved rather than linear.

a. One transformation that might result in a relationship that is more nearly linear is log(y). The values of x 5 number of days since injection of cancer cells, y 5 average tumor volume (in mm3 ), and y 5 log(y)
for the 0.2% PFE group are given in the accompanying table. Construct a scatterplot of y versus x. Does this scatterplot look more nearly linear than the plot of the original data?
Days After Injection x 0.2% PFE Average Tumor Size y Log(y)
11 40 1.60 15 75 1.88 19 90 1.95 23 210 2.32 27 230 2.36 31 330 2.52 35 450 2.65 39 600 2.78

b. Based on the accompanying Minitab output, does the least-squares line effectively summarize the relationship between y and x?
The regression equation is log(average tumor size) 1.23

 0.0413 Days After Injection Predictor Coef SE Coef T P Constant 1.22625 0.07989