# 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