MSMU (version 0.1.2)

position_stats: Computes Position Statics, Quintiles and Quartiles

Description

Calculates the quintiles, including quartiles(data is split in 4 equal parts) and quintiles(data is split in 5 equal parts) of a numeric vector using the 'quantile()' function. NA's are removed.

Usage

position_stats(x)

Value

A list with two elements:

quint

Numeric vector of quintiles (0%, 20%, 40%, ..., 100%)

quart

Numeric vector of quartiles (0%, 25%, 50%, 75%, 100%)

Arguments

x

A numeric vector.

Details

Percentiles are values that divide a dataset into 100 equal parts, each representing 1% of the distribution. For example, the 25th percentile is the value below which 25% of the data fall.

Quartiles are special percentiles that divide the data into four equal groups: Q1 (25th percentile), Q2 (50th percentile or median), Q3 (75th percentile).

Quintiles divide data into five equal groups, each representing 20% of the distribution: 20th percentile, 40th, 60th, 80th percentiles split the data into quintiles.

Examples

# Position stats of random data
set.seed(123)
x <- rnorm(1000)
position_stats(x)

# Position stats of MPG in mtcars data set
data("mtcars")
position_stats(mtcars$mpg)