when to use a log log regression model?
the book says whenever the dependent variable bears a contstant propotional relationship with independent variable
can some1 explain it more clearly?
If
y = c(x^m)
then
log(y) = log[c(x^m)] = log(c) + m log(x)
If we let Y = log(y), b = log(c), and X = log(x), then we have:
Y = mX + b
which is a straight line.
ok so if the relationship is something which is explained by raising the dependent variable to a power than we use log log reg. model?
Yup.