> ## Table 9.5, 9.6 and 9.7
> dat=read.table("table9_5.dat")
> dat
   V1    V2    V3    V4
1   1 -1.00 -1.00 91.21
2   2 -1.00  1.00 94.17
3   3  1.00 -1.00 87.46
4   4  1.00  1.00 94.38
5   5  0.00  0.00 93.04
6   6  0.00  0.00 93.06
7   7 -1.41  0.00 93.56
8   8  1.41  0.00 91.17
9   9  0.00 -1.41 88.74
10 10  0.00  1.41 95.08
> time=dat[,2]
> temp=dat[,3]
> yield=dat[,4]
> g=lm(yield ~ time + temp + time:temp + I(time^2), subset=1:6)  # model 
(9.12) using the first 6 runs only
> summary(g)  # Table 9.6 

Call:
lm(formula = yield ~ time + temp + time:temp + I(time^2), subset = 1:6)

Residuals:
         1          2          3          4          5          6 
-7.005e-19  6.717e-19  7.648e-19 -1.003e-18 -1.000e-02  1.000e-02 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 93.050000   0.010000  9305.0 6.84e-05 ***
time        -0.885000   0.007071  -125.2  0.00509 ** 
temp         2.470000   0.007071   349.3  0.00182 ** 
I(time^2)   -1.245000   0.012247  -101.7  0.00626 ** 
time:temp    0.990000   0.007071   140.0  0.00455 ** 
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 

Residual standard error: 0.01414 on 1 degrees of freedom
Multiple R-Squared:     1,	Adjusted R-squared:     1 
F-statistic: 4.19e+04 on 4 and 1 DF,  p-value: 0.003664 

> 
> g=lm(yield ~ time + temp + time:temp + I(time^2) + I(temp^2))  # model 
(9.5) using all 10 runs
> summary(g)  # Table 9.7 (the results are slightly different, probably 
due to rounding)

Call:
lm(formula = yield ~ time + temp + time:temp + I(time^2) + I(temp^2))

Residuals:
        1         2         3         4         5         6         7 
-0.254408 -0.033297 -0.291778 -0.070667 -0.011946  0.008054  0.137006 
        8         9        10 
 0.190014  0.320327  0.006694 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 93.05195    0.19802 469.918 1.23e-10 ***
time        -0.86631    0.09916  -8.737 0.000946 ***
temp         2.35944    0.09916  23.795 1.85e-05 ***
I(time^2)   -0.42777    0.13148  -3.254 0.031271 *  
I(temp^2)   -0.65664    0.13148  -4.994 0.007521 ** 
time:temp    0.99000    0.14002   7.070 0.002111 ** 
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 

Residual standard error: 0.28 on 4 degrees of freedom
Multiple R-Squared: 0.9945,	Adjusted R-squared: 0.9876 
F-statistic: 143.8 on 5 and 4 DF,  p-value: 0.0001332