Why Do Percentiles Begin at the 1st instead of 0th?

Why percentiles start at 1 instead of 0? Explore statistical conventions and history behind percentiles in this informative article.

Why Do Percentiles Begin at the 1st instead of 0th?
Photo by National Cancer Institute / Unsplash

When delving into the captivating realm of statistics, the concept of percentiles often baffles many.

Despite its label from the 1st to the 99th percentile, it essentially segments the population into 99 parts rather than 100.

This unconventional convention sparks curiosity, leading to a quest for its origins.

Understanding Percentiles

Traditionally, percentiles represent values below which a certain percentage of data falls.

For instance, being in the 90th percentile means 90% of scores are lower than yours.

Despite this, the question lingers - why does this system start at the 1st percentile and not at 0% or 0th percentile?

Searching for Logic in the Percentage

To decipher this enigma, let's consider an example involving a population of 1000 test takers.

If the top 10 are in the 99th percentile and the bottom 10 in the 1st percentile, what do we make of the 11th lowest and highest ranks?

Exploring Various Theories

The traditional explanation revolves around the notion of 'percentage of people below you,' yet it fails to provide a satisfying rationale for excluding the 0th and 100th percentiles.

Some argue that the exclusion is rooted in mathematical convention to avoid confusion, while others relate it to the calculation methods employed in statistics.

A Tale of Centuries and Centiles

The conventions and premises of percentiles intertwine with centuries-old statistical practices.

Their origins can be traced to the works of renowned statisticians and mathematicians throughout history, each contributing to the development and standardization of statistical measures that we employ today.

The Evenness Dilemma

The absence of the 0th and 100th percentiles may continue to perplex many minds.

It urges a critical reflection on the standardization of statistical terminologies and the possibility of adapting to a more inclusive approach aligning with the 100-part division of a population.