Grubbs test and checking outliers

In statistics, or particularly in R programming, an outlier is defined as an observation that is far removed from most of the other observations. Often, an outlier is present due to a measurement error.

The following script is used to detect the particular outliers for each and every attribute:

> outlierKD <- function(dt, var) {
+ 
          var_name <- eval(substitute(var),eval(dt))
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          na1 <- sum(is.na(var_name))
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          m1 <- mean(var_name, na.rm = T)
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          par(mfrow=c(2, 2), oma=c(0,0,3,0))
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          boxplot(var_name, main="With outliers")
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          hist(var_name, main="With outliers", xlab=NA, ylab=NA)
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          outlier <- boxplot.stats(var_name)$out
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          mo <- mean(outlier)
          + 
          var_name &lt...