# 不同颜色的饮料的销量数据(样本容量相同,结果显著)
data=rbind(
data.frame(color="nocolor" ,sale=c(26.5,28.7,25.1,29.1,27.2)),
data.frame(color="pink" ,sale=c(31.2,28.3,30.8,27.9,29.6)),
data.frame(color="orange" ,sale=c(27.9,25.1,28.5,24.2,26.5)),
data.frame(color="green" ,sale=c(30.8,29.6,32.4,31.7,32.8))
);
# 统计各组均值
aggregate(data$sale,by=list(data$color),FUN=mean)
# 统计各组标准差
aggregate(data$sale,by=list(data$color),FUN=sd)
fit=aov(sale~color,data=data)
summary(fit)

# 对老师评分ABCD的学生对应的成绩(样本容量不相同,结果不显著)
data=rbind(
data.frame(comment="A" ,grade=c(85,77,79,84,92,90,73)),
data.frame(comment="B" ,grade=c(80,78,94,73,79,86,91,75,81,64)),
data.frame(comment="C" ,grade=c(73,80,92,76,6)),
data.frame(comment="D" ,grade=c(76,72,70,85))
);
aggregate(data$grade,by=list(data$comment),FUN=mean)
# 统计各组标准差
aggregate(data$grade,by=list(data$comment),FUN=sd);
fit=aov(grade~comment,data=data);
summary(fit)