What 's the value added?
The problem of bad model predictions is still an open issue. This time, you investigate the relation between log(SALES)
and PRICE
. The corresponding scatterplot is created using the formula argument log(SALES) ~ PRICE
in the plot()
function. Again, the model predictions obtained from the log.model
are graphed using the abline()
function. The abline()
function adds a straight line specified in log-sales intercept/ price slope form when applied to the log.model
object .
Diese Übung ist Teil des Kurses
Building Response Models in R
Anleitung zur Übung
- Display the relation between
log(SALES)
andPRICE
in a simple scatterplot. - Again, explain
log(SALES)
byPRICE
and assign the result to an object namedlog.model
. - Add the model predictions by applying the function
abline()
to thelog.model
object.
Interaktive Übung
Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.
# Plot log(SALES) against PRICE
___(___, data = sales.data)
# Explain log(SALES) by PRICE
log.model <- ___(___, data = sales.data)
# Add the model predictions