problem-3.32

problem-3.32  From the scatterplot we see that four temperatures were used. It appears that only one data point is associated with a temperature of 150, but in fact there were ten:
> table(motors$temp)

150 170 190 220
 10  10  10  10
    
It is hard to tell whether the values for this temperature fit a linear model. Assuming they do, we can fit the model with
> res = lm(time ~ temp,  data=motors)
> res

Call:
lm(formula = time ~ temp, data = motors)

Coefficients:
(Intercept)         temp
      22999         -107
    
Then predictions can be made using predict():
> predict(res, newdata=data.frame(temp=210))
[1] 580.6