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### How to implement One Way ANOVA in R?

###### Description

To implement the one way ANOVA using R programming.

###### Process
One Way ANOVA:
• Compares means of more than two independent groups.
Hypothesis:
• H0: Means of different groups are same
• H1: Atleast one sample mean is not equal to others
Assmptions of One-Way ANOVA:
• Groups are independent with each other
• Data of each group are normally distributed
• Normal Population should have common variance
R Functions :
• R Function :aov(formula)
• formula -- a formula specifying the model
• R Function : TukeyHSD(x) -- to evaluate pair means
• x -- a fitted model object, usually
Interpretation of plotted pairwise t test :
• Significant differences are the ones which not cross the zero value.
###### Sapmle Code

#One way ANOVA
#Input
View(iris)
input<-iris\$Sepal.Width
input1<-iris\$Species

#Box Plot
boxplot(input~input1,col=c(“green”,”yellow”,”blue”),horizontal=FALSE)
title(main = “Box Plot”,xlab = “Species”,ylab = “Petal.Width”)

#Normality of data of each group
#Histogram
#install.packages(“FSA”)
library(“FSA”)
hist(Sepal.Length~Species,data=iris,col=c(“red”,”yellow”,”blue”))

#Mean value
mean_val<-round(tapply(input,input1,mean),digits = 2)
print(mean_val)

#Plotting Means
#install.packages(“gplots”)
library(“gplots”)
plotmeans(input~input1,col = “red”,mean.labels = TRUE,pos=4,xlab = “Species”,ylab = “Petal Width”,main=”Plot of Petal Width means by Species”,pch=15,cex=1)