# Statistics tutor

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MCAR is an acronym for Missing Completely at Random MNAR means Missing not at Random When you have data missing you may try to check if this missing data is random or not. Usually this is done by checking the… Continue Reading →

Spearman rank correlation method Better use when: variables are not normally distributed or the relationship between the variables is not linear

To remove a column from a R dataframe you have to check what is the column number and then give command like data<-data[,-1] The number will be the column to be deleted.

The correlation coefficient of two variables in a data sample is their covariance divided by the product of their individual standard deviations. It is a normalized measurement of how the two are linearly related with values beetween -1 and 1. To calculate… Continue Reading →

You can use function lapply() to apply function summary() to each column and then cbind() to show data as column. lapply(dataFrame,function(x) cbind(summary(x))) From http://stackoverflow.com/questions/14791075/r-format-data-frame-summary

http://www.r-bloggers.com/more-on-exploring-correlations-in-r/ cor() – table of correlations cor.prob() – Replaces the upper triangul with the significance flattenSquareMatrix(cor.prob(mydata)) – makes a table out of it   flattenSquareMatrix <- function(m) { if( (class(m) != “matrix“) | (nrow(m) != ncol(m))) stop(“Must be a square… Continue Reading →

To pass a dataframe in R to matrix as.matrix(mtcars) Some commands work over matrix and not over dataframes