Measures of Position in Statistics

In the last tutorials, we have learned about the measures of location and dispersion in detail. In this tutorial, we will learn about the measures of position – another technique for measuring dispersions.

Although the standard deviations are the widely used measure of dispersion that belongs to measures of location. But there are some other methods that also can be applied for measuring the dispersion or variation in a data set. That is the measure of position.

What is Measures of Position?

The measure of position is actually a tactic for measuring dispersion in a data set. These measurements include quartiles, deciles, and percentiles.

Quartiles divide a set of data into four equal parts. In the quartiles measurement, as the observations are divided into four equals part that’s why it makes three breakdowns in the observations at the position of 25%, 50%, and 75%. And these breakdowns are labeled as Q1, Q2, and Q3.

quartiles measures of position

Deciles divide a set of data into ten equal parts. In the deciles measurement, as the observations are divided into ten equals part that’s why it makes nine breakdowns in the observations at the position of 10%, 20%, 30%, … 90%. And these breakdowns are labeled as D1, D2, D3, …. D9.

deciles measure of position

Percentiles divide a set of data into a hundred equal parts. In the percentiles measurement, as the observations are divided into a hundred equals part that’s why it makes 99 breakdowns in the observations at the position of every percent (1%, 2%, 3%, …. 99%). And these breakdowns are labeled as P1, P2, P3, …. P99.

percentiles measures of position

Quartiles vs Deciles vs Percentiles

In the different scenarios of measurement, you will use different methods. When you will measure the average or central tendency of 25%, 50%, or 75%, then using the quartiles method is the best solution. In the same way, if you want to measure 10%, 20%, 70%, etc then obviously deciles will be the best approach.

And in the last situations, if you need to calculate the measures like 17%, 23%, 94%, etc then Percentile comes in handy in this case.

NOTE: Quartiles, deciles, and percentiles are only applicable for ungrouped and numerically sorted data set. Any unsorted data should be sorted before calculations.

What is next?

In the next subsequent tutorials, we will learn about the quartiles, deciles, and percentiles in detail with their measurement rules, formula, and example math.

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