The best$-$fitting advertising response function in Example $7\mathrm{.}5$ fits the observed data. This is because we chose the observed data to fall close to a curve of the form in Equation $(7\mathrm{.}4).$ See what happens when one of the observed points is an outlier$-$that is$,$ it doesn't fit the pattern of the others.

$$Specifically$,$ change the number of exposures corresponding to $50$ ads from $90\mathrm{.}3$ to $125,$ and then rerun Solver. Do you get essentially the same response function as before, or does this one outlier exert a large influence on the estimated response function?

$$Repeat part a$,$ but now change the number of exposures corresponding to $50$ ads from $90\mathrm{.}3$ to $55.$