Percentile vs. Quantile — What's the Difference?

A measure indicating the value below which a given percentage of observations in a group of observations falls.

A generic term for dividing a probability distribution into equal-sized, continuous intervals.

Helps in understanding distributions of scores or measurements.

Includes specific cases like quartiles, deciles, percentiles.

Reflects relative standing within a dataset.

Can be tailored to the needs of the analysis.

Used to compare and rank individuals in a population.

Helps in identifying outliers and data trends.

Applies to standardized testing and measurements.

Useful in statistical analyses to summarize data distributions.

In statistics, a percentile (or a centile) is a score below which a given percentage of scores in its frequency distribution falls (exclusive definition) or a score at or below which a given percentage falls (inclusive definition). For example, the 50th percentile (the median) is the score below which (exclusive) or at or below which (inclusive) 50% of the scores in the distribution may be found.

In statistics and probability, quantiles are cut points dividing the range of a probability distribution into continuous intervals with equal probabilities, or dividing the observations in a sample in the same way. There is one fewer quantile than the number of groups created.

Each of the 100 equal groups into which a population can be divided according to the distribution of values of a particular variable.

Each of any set of values of a variate which divide a frequency distribution into equal groups, each containing the same fraction of the total population.

Any of the groups that result when a frequency distribution is divided into 100 groups of equal size.

(statistics) One of the class of values of a variate which divides the members of a batch or sample into equal-sized subgroups of adjacent values or a probability distribution into distributions of equal probability.

Any of the values that separate each of these groups.

(statistics) Any of the ninety-nine points that divide an ordered distribution into one hundred parts, each containing one per cent of the population.

(statistics) Any one of the hundred groups so divided.

(statistics) any of the 99 numbered points that divide an ordered set of scores into 100 parts each of which contains one-hundredth of the total

A percentile is a specific type of quantile that divides the dataset into 100 equal parts, focusing on detailed ranking within the data.

Percentiles can provide more granular insights compared to quartiles, which divide data into four parts, by offering a finer comparison across the dataset.

While percentiles mainly rank and compare individual scores, significant differences between percentiles (e.g., between the 25th and 75th) can hint at data skewness.

Quantiles, including quartiles and percentiles, are used to describe the distribution, identify outliers, and understand trends within a dataset.

Quantiles are crucial in statistical modeling for assessing the probability distribution of data, evaluating model performance across different parts of the data distribution, and managing outliers.

The median is both a percentile (the 50th percentile) and a quantile (specifically, a 2-quantile), representing the middle value of a dataset.

Percentiles in standardized test scores show how a test taker's score compares to others, indicating the percentage of people the test taker scored better than.

Yes, quartiles are a specific type of quantile that divide the dataset into four equal parts, each representing a key distribution point (25th, 50th, 75th percentiles).

A researcher might choose quantiles for flexibility in analysis, allowing for data division that's more suited to the specific context or research question.

The choice impacts the granularity of analysis; percentiles provide more detailed ranking information, while quantiles offer broader data segmentation, affecting insights into distribution and variance.