Statistical Aggregation Functions

Overview

Expand each Function name for a brief description and the syntax.

Statistical Aggregation Functions in Chart Expressions

Avg Avg() returns the aggregated average of the Expression or field iterated over the chart Dimensions. Syntax: avg({[SetExpression] [DISTINCT] [TOTAL [<fld{, fld}>]]} expr)

Correl Correl() returns the aggregated correlation coefficient for two data sets. The correlation function is a measure of the relationship between the data sets and is aggregated for (x,y) value pairs iterated over the chart Dimensions. Syntax: correl({[SetExpression] [TOTAL [<fld {, fld}>]]} value1, value2 )

Fractile Fractile() finds the value that corresponds to the fractile (quantile) of the aggregated data in the range given by the Expression iterated over the chart Dimensions. Syntax: fractile({[SetExpression] [TOTAL [<fld {, fld}>]]} expr, fraction)

Kurtosis Kurtosis() finds the kurtosis of the range of data aggregated in the Expression or field iterated over the chart Dimensions. Syntax: kurtosis({[SetExpression] [DISTINCT] [TOTAL [<fld{, fld}>]]} expr)

LINEST_B LINEST_B() returns the aggregated b value (y-intercept) of a linear regression defined by the equation y=mx+b for a series of coordinates represented by paired numbers in the Expressions given by the Expressions x_value and y_value, iterated over the chart Dimensions. Syntax: linest_r2({[SetExpression] [TOTAL [<fld{ ,fld}>]] }y_value, x_value[, y0_const[, x0_const]])

LINEST_df LINEST_DF() returns the aggregated degrees of freedom of a linear regression defined by the equation y=mx+b for a series of coordinates represented by paired numbers in the Expressions given by x_value and y_value, iterated over the chart Dimensions. Syntax: linest_df({[SetExpression] [TOTAL [<fld{, fld}>]]} y_value, x_value [, y0_const [, x0_const]])

LINEST_f LINEST_F() returns the aggregated F statistic (r2/(1-r2)) of a linear regression defined by the equation y=mx+b for a series of coordinates represented by paired numbers in the Expressions given by x_value and the y_value, iterated over the chart Dimensions. Syntax: linest_f({[SetExpression] [TOTAL[<fld{, fld}>]]} y_value, x_value [, y0_const [, x0_const]])

LINEST_M LINEST_M() returns the aggregated m value (slope) of a linear regression defined by the equation y=mx+b for a series of coordinates represented by paired numbers given by the Expressions x_value and y_value, iterated over the chart Dimensions. Syntax: linest_m({[SetExpression] [TOTAL[<fld{, fld}>]]} y_value, x_value [, y0_const [, x0_const]])

LINEST_r2 LINEST_R2() returns the aggregated r2 value (coefficient of determination) of a linear regression defined by the equation y=mx+b for a series of coordinates represented by paired numbers given by the Expressions x_value and y_value, iterated over the chart Dimensions. Syntax: linest_r2({[SetExpression] [TOTAL [<fld{ ,fld}>]] }y_value, x_value[, y0_const[, x0_const]])

LINEST_seb LINEST_SEB() returns the aggregated standard error of the b value of a linear regression defined by the equation y=mx+b for a series of coordinates represented by paired numbers given by the Expressions x_value and y_value, iterated over the chart Dimensions. Syntax: linest_seb({[SetExpression] [TOTAL [<fld{ ,fld}>]] }y_value, x_value[, y0_const[, x0_const]])

LINEST_sem LINEST_SEM() returns the aggregated standard error of the m value of a linear regression defined by the equation y=mx+b for a series of coordinates represented by paired numbers given by the Expressions x_value and y_value, iterated over the chart Dimensions. Syntax: linest_sem([{set_Expression}][ distinct ] [total [<fld {,fld}>] ] y-Expression, x-Expression [, y0 [, x0 ]] )

LINEST_sey LINEST_SEY() returns the aggregated standard error of the y estimate of a linear regression defined by the equation y=mx+b for a series of coordinates represented by paired numbers given by the Expressions x_value and y_value, iterated over the chart Dimensions. Syntax: linest_sey({[SetExpression] [TOTAL [<fld{ ,fld}>]] }y_value, x_value[, y0_const[, x0_const]])

LINEST_ssreg LINEST_SSREG() returns the aggregated regression sum of squares of a linear regression defined by the equation y=mx+b for a series of coordinates represented by paired numbers given by the Expressions x_value and y_value, iterated over the chart Dimensions. Syntax: linest_ssreg({[SetExpression] [TOTAL [<fld{ ,fld}>]] }y_value, x_value[, y0_const[, x0_const]])

LINEST_ssresid LINEST_SSRESID() returns the aggregated residual sum of squares of a linear regression defined by the equation y=mx+b for a series of coordinates represented by paired numbers in the Expressions given by x_value and y_value, iterated over the chart Dimensions. Syntax: linest_ssresid({[SetExpression] [TOTAL [<fld{ ,fld}>]] }y_value, x_value[, y0_const[, x0_const]])

Median Median() returns the median value of the range of values aggregated in the Expression iterated over the chart Dimensions. Syntax: median({[SetExpression] [TOTAL [<fld{, fld}>]]} expr)

Skew Skew() returns the aggregated skewness of the Expression or field iterated over the chart Dimensions. Syntax: skew{[SetExpression] [DISTINCT] [TOTAL [<fld{ ,fld}>]]} expr)

Stdev Stdev() finds the standard deviation of the range of data aggregated in the Expression or field iterated over the chart Dimensions. Syntax: stdev({[SetExpression] [DISTINCT] [TOTAL [<fld{, fld}>]]} expr)

Sterr Sterr() finds the value of the standard error of the mean, (stdev/sqrt(n)), for the series of values aggregated in the Expression iterated over the chart Dimensions. Syntax: sterr({[SetExpression] [DISTINCT] [TOTAL[<fld{, fld}>]]} expr)

STEYX STEYX() returns the aggregated standard error when predicting y-values for each x-value in a linear regression given by a series of coordinates represented by paired numbers in the Expressions given by y_value and x_value. Syntax: steyx{[SetExpression] [TOTAL [<fld{, fld}>]]} y_value, x_value)