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How to use shapiro wilk test to check normality of an R data frame column?
To apply shapiro wilk test for normality on vectors, we just simply name the vector inside shapiro.test function but if we want to do the same for an R data frame column then the column will have to specify the column in a proper way. For example, if the data frame name is df and the column name is x then the function will work as shapiro.test(df$x).
Example
x1<-rnorm(1000,1.5) df1<-data.frame(x1) shapiro.test(df1$x1)
Output
Shapiro-Wilk normality test data: df1$x1 W = 0.99886, p-value = 0.792
Example
x2<-runif(1000,2,10) df2<-data.frame(x2) shapiro.test(df2$x2)
Output
Shapiro-Wilk normality test data: df2$x2 W = 0.9581, p-value = 2.562e-16
Example
x3<-rpois(4000,2) df3<-data.frame(x3) shapiro.test(df3$x3)
Output
Shapiro-Wilk normality test data: df3$x3 W = 0.91894, p-value < 2.2e-16
Example
x4<-rpois(4000,5) df4<-data.frame(x4) shapiro.test(df4$x4)
Output
Shapiro-Wilk normality test data: df4$x4 W = 0.97092, p-value < 2.2e-16
Example
x5<-sample(1:5,5000,replace=TRUE) df5<-data.frame(x5) shapiro.test(df5$x5)
Output
Shapiro-Wilk normality test data: df5$x5 W = 0.88902, p-value < 2.2e-16
Example
x6<-sample(1:10,5000,replace=TRUE) df6<-data.frame(x6) shapiro.test(df6$x6)
Output
Shapiro-Wilk normality test data: df6$x6 W = 0.93373, p-value < 2.2e-16
Example
x7<-sample(1:100,5000,replace=TRUE) df7<-data.frame(x7) shapiro.test(df7$x7)
Output
Shapiro-Wilk normality test data: df7$x7 W = 0.9556, p-value < 2.2e-16
Example
x8<-sample(2500:3500,5000,replace=TRUE) df8<-data.frame(x8) shapiro.test(df8$x8)
Output
Shapiro-Wilk normality test data: df8$x8 W = 0.95117, p-value < 2.2e-16
Example
x9<-rbinom(5000,10,0.5) df9<-data.frame(x9) hapiro.test(df9$x9)
Output
Shapiro-Wilk normality test data: df9$x9 W = 0.96629, p-value < 2.2e-16
Example
x10<-rbinom(5000,1000,0.5) df10<-data.frame(x10) shapiro.test(df10$x10)
Output
Shapiro-Wilk normality test data: df10$x10 W = 0.9993, p-value = 0.04748
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