library(car)
W0=data.frame(Wool);        ### lecture du tableau de donn�es "Wool"
ind=c(10:18);
W=W0[ind,];  #  on consid�re seulement les  observations 10-18
attach(W);
cat("Le contenu du tableau W est: \n")
print(W);
cat("\n Test de shapiro sur la variable cycles \n ")
shapiro.test(cycles)
amp=factor(amp);
load=factor(load);
m1=lm(cycles~amp+load, contrasts=list(amp=contr.sum, load=contr.sum))
cat("\n SUMMARY  \n")
print(summary(m1))
cat("\n ANOVA DE TYPE III \n ")
print(Anova(m1,type="III"))

############################################################################

Le contenu du tableau W est: 
   len amp load cycles
10 300   8   40   1414
11 300   8   45   1198
12 300   8   50    634
13 300   9   40   1022
14 300   9   45    620
15 300   9   50    438
16 300  10   40    443
17 300  10   45    332
18 300  10   50    220

 Test de shapiro sur la variable cycles 
 
	Shapiro-Wilk normality test

data:  cycles
W = 0.9099, p-value = 0.315


 SUMMARY  

Call:
lm(formula = cycles ~ amp + load, contrasts = list(amp = contr.sum, 
    load = contr.sum))

Residuals:
      1       2       3       4       5       6       7       8       9 
  74.67  101.67 -176.33   71.33  -87.67   16.33 -146.00  -14.00  160.00 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   702.33      54.56  12.873  0.00021 ***
amp1          379.67      77.16   4.921  0.00793 ** 
amp2           -9.00      77.16  -0.117  0.91276    
load1         257.33      77.16   3.335  0.02897 *  
load2          14.33      77.16   0.186  0.86167    
---
Signif. codes:  0 �***� 0.001 �**� 0.01 �*� 0.05 �.� 0.1 � � 1

Residual standard error: 163.7 on 4 degrees of freedom
Multiple R-squared:  0.9219,	Adjusted R-squared:  0.8439 
F-statistic: 11.81 on 4 and 4 DF,  p-value: 0.01733


 ANOVA DE TYPE III 
 Anova Table (Type III tests)

Response: cycles
             Sum Sq Df  F value  Pr(>F)    
(Intercept) 4439449  1 165.7170 0.00021 ***
amp          844865  2  15.7687 0.01267 *  
load         420686  2   7.8517 0.04121 *  
Residuals    107157  4                     
---
Signif. codes:  0 �***� 0.001 �**� 0.01 �*� 0.05 �.� 0.1 � � 1