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Rforch17 - R Material for Chapter 17 > data.sales16

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R Material for Chapter 17 > data.sales16 <- read.table(file=" http://www.stat.ufl.edu/~rrandles/sta4211/Rclassnotes/data/data16- 1.txt ",col.names=c("sales","package","repl")) ## reading in the data > data.sales16 sales package repl 1 11 1 1 2 17 1 2 3 16 1 3 4 14 1 4 5 15 1 5 6 12 2 1 7 10 2 2 8 15 2 3 9 19 2 4 10 11 2 5 11 23 3 1 12 20 3 2 13 18 3 3 14 17 3 4 15 27 4 1 16 33 4 2 17 22 4 3 18 26 4 4 19 28 4 5 > attach(data.sales16) > boxplot(sales~package,data.sales16) ## draw a boxplot of the four data sets > fpack <- factor(package) ## make package a factor > model <- aov(sales~fpack,data=data.sales16) ## run the anova model on this data > summary(model) Df Sum Sq Mean Sq F value Pr(>F) fpack 3 588.22 196.074 18.591 2.585e-05 *** Residuals 15 158.20 10.547 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > res <- residuals(model) > res 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 -3.6 2.4 1.4 -0.6 0.4 -1.4 -3.4 1.6 5.6 -2.4 3.5 0.5 -1.5 -2.5 -0.2 5.8 17 18 19 -5.2 -1.2 0.8 > with(data.sales16, tapply(sales,fpack,mean)) ## sample means for each factor level 1 2 3 4 14.6 13.4 19.5 27.2 > with(data.sales16, tapply(sales,fpack,sd)) ## sample std deviations for each factor level 1 2 3 4 2.302173 3.646917 2.645751 3.962323
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  • Spring '08
  • Randles
  • Df Sum Sq, Studentized range, Turkish Radio and Television Corporation, Bonferroni Method, sample std deviations, Honest Significant Difference

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