This isn't exactly what we're looking for. Suppose that when you plot
the hypothetical raw data (x,y) using
plot(x,y)
it looks like Y is roughly equal to log(X) plus random noise. Then
transforming the x variable to be log(x) should result in a roughly
linear relationship
plot(log(x), y)
Obviously if the relationship is not logarithmic this transformation
won't work, but you get the idea.
Let me know if this is not clear.
Hope this helps.
Best,
Kevin
I'm trying to graph the transformations in 1.
I've consulted the book and
section notes, but I'm not sure if I'm correct. For 1a, I have the following
code for the transformation:
library(car)
library(mgcv)
data(Sahlins)
s2<-na.omit(Sahlins)
attach(s2)
par(mfrow=c(2,2))
lm.out2<-lm(log(consumers)~acres+(acres)^2)
qq.plot(lm.out2, main="Linear transformation of Consumers to Acres")
I get a linear relationship, but I'm not sure this is the format
you're looking for...?