Returns the sample p-quantile of the non-missing observations (i.e. divides the sample data into equal parts determined by the percentage p).
X is the input data sample (one/two dimensional array of cells (e.g. rows or columns))
p is a scalar value between 0 and 1.
- The time series may include missing values (e.g. #N/A, #VALUE!, #NUM!, empty cell), but they will not be included in the calculations.
- The Quantile function for any distribution is defined between 0 and 1. Its function is the inverse of the cumulative distribution function (CDF).
- The Quantile function returns the sample median when $p=0.5$.
- The Quantile function returns the sample minimum when $p=0$.
- The Quantile function returns the sample maximum when $p=1$.
- For any probability distribution, the following holds true for the probability $p$ :
$$P(X\lt q)\geq p$$
- $q$ is the sample $p$-quantile
|=Quantile($B$2:$B$30,0.5)||Sample median (-0.69)|
|=Quantile($B$2:$B$30,0)||Sample minimum (-2.18)|
|=Quantile($B$2:$B$30,1)||Sample maximum (1.73)|