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HW4_STA5166 - a This is a randomized Bloack experimental...

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a) This is a randomized Bloack experimental design b) Analyzing each of the paint suppliers, the mean is different for each of them as illustrated above. > fit1= aov(y~supplier + site, data=Prob4.1) Warning message: variable 'site' converted to a factor in: model.matrix.default(mt, mf, contrasts) > fit2= aov(y~supplier, data=Prob4.1) > summary(fit1) Df Sum Sq Mean Sq F value Pr(>F) supplier 3 665.13 221.71 20.387 1.503e-05 *** site 5 568.71 113.74 10.459 0.0001808 *** Residuals 15 163.13 10.88 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
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attributes(fit1) par(mfrow=c(1,1)) plot(fit1$fitted.values, fit1$residuals) 55 60 65 70 75 -2 0 2 4 6 fit1$fitted.values fit1$residuals Analyzing the residuals, assume no effect since no pattern and wide spread. Using S-Plus Using R ##load package mvtnorm ##load package multcomp ##load package multtest int= glht(fit2, linfct = mcp(supplier = "Tukey")) int print(confint(int)) plot(confint(int)) summary(int, test = adjusted( "bonferroni")) #this gives same output as glht ##with site summary(simtest(y~supplier + site, data = Prob4.1, whichf="supplier",type = "Tukey")) summary(simint(y~supplier+site, data = Prob4.1,whichf="supplier",type = "Tukey"))
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