## R: Calculate Mean, Median, Mode, Variance, Standard Deviation

This article shows how to calculate Mean, Median, Mode, Variance, and Standard Deviation of any data set using R programming language.

**Mean:** Calculate sum of all the values and divide it with the total number of values in the data set.

1 2 3 4 | > x <- c(1,2,3,4,5,1,2,3,1,2,4,5,2,3,1,1,2,3,5,6) # our data set > mean.result = mean(x) # calculate mean > print (mean.result) [1] 2.8 |

**Median:** The middle value of the data set.

1 2 3 4 | > x <- c(1,2,3,4,5,1,2,3,1,2,4,5,2,3,1,1,2,3,5,6) # our data set > median.result = median(x) # calculate median > print (median.result) [1] 2.5 |

**Mode:** The most occurring number in the data set. For calculating mode, there is no default function in R. So, we have to create our own custom function.

1 2 3 4 5 6 7 8 9 10 | > mode <- function(x) { + ux <- unique(x) + ux[which.max(tabulate(match(x, ux)))] + } > x <- c(1,2,3,4,5,1,2,3,1,2,4,5,2,3,1,1,2,3,5,6) # our data set > mode.result = mode(x) # calculate mode (with our custom function named ‘mode’) > print (mode.result) [1] 1 |

**Variance:** How far a set of data values are spread out from their mean.

1 2 3 | > variance.result = var(x) # calculate variance > print (variance.result) [1] 2.484211 |

**Standard Deviation:** A measure that is used to quantify the amount of variation or dispersion of a set of data values.

1 2 3 | > sd.result = sqrt(var(x)) # calculate standard deviation > print (sd.result) [1] 1.576138 |

Hope this helps. Thanks.