Statistical Scalar Functions

Table 129. Statistical Scalar Functions 

Function

Description

Median (numbers, break)

Returns the median of a column of numbers.

Median example

Mode (numbers, break_col)

Returns the most frequently occurring value in a column of numbers.

Mode example

Percentile (numbers, n, break_col)

Returns the nth percentile of values in a column of numbers in ascending order.

Percentile example

Rank (numbers, break_col)

Returns the rank of a number in a column of numbers.

Rank example

There is a restriction on setting a filter on an aggregate column (which “Rank” is considered). To set a filter on the column, insert a new table into the Interactive Reporting document file and drag the columns into the table data layout. This creates a “copy” of the columns which can have a filter set on it.

RankAsc (numbers, break_col)

Returns the rank of a number in a column of numbers in ascending order.

RankAsc example

StdDev (numbers, break_col)

Estimates standard deviation based on a sample. The standard deviation is a measure of how widely values are dispersed from the average value (the mean). If your data represents the entire population, then compute the standard deviation using the StdDevp function.

StdDev example

StdDevp (numbers, break_col)

Calculates standard deviation based on the entire population given as arguments. The standard deviation is a measure of how widely values are dispersed from the average value (the mean). If your data represents a sample of the population, then compute the standard deviation using the StdDev function.

StdDevp example

Var (numbers, break_col)

Estimates variance based on a sample. The Var function assumes that its arguments are a sample of the population. If your data represents the entire population, then compute the variance using the Varp function.

Var example

Varp (numbers, break_col)

Estimates variance based on the entire population. The Varp function assumes that its arguments are the entire population. If your data represents a sample of the population, then compute the variance using the Var function.

Varp example