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LINEST_M - chart function


LINEST_M - chart function

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.


LINEST_M([{SetExpression}] [DISTINCT] [TOTAL [<fld{, fld}>]] y_value, x_value [, y0_const [, x0_const]])

Return data type: numeric


Argument Description
y_value The expression or field containing the range of y-values to be measured.
x_value The expression or field containing the range of x-values to be measured.
y0, x0 An optional value y0 may be stated forcing the regression line to pass through the y-axis at a given point. By stating both y0 and x0 it is possible to force the regression line to pass through a single fixed coordinate.
Note: Unless both y0 and x0 are stated, the function requires at least two valid data-pairs to calculate. If y0 and x0 are stated, a single data pair will do. 
SetExpression By default, the aggregation function will aggregate over the set of possible records defined by the selection. An alternative set of records can be defined by a set analysis expression.
DISTINCT If the word DISTINCT occurs before the function arguments, duplicates resulting from the evaluation of the function arguments are disregarded.

If the word TOTAL occurs before the function arguments, the calculation is made over all possible values given the current selections, and not just those that pertain to the current dimensional value, that is, it disregards the chart dimensions.

By using TOTAL [<fld {.fld}>], where the TOTAL qualifier is followed by a list of one or more field names as a subset of the chart dimension variables, you create a subset of the total possible values.

Defining the aggregation scope


The expression must not contain aggregation functions, unless these inner aggregations contain the TOTAL qualifier. For more advanced nested aggregations, use the advanced aggregation function Aggr, in combination with calculated dimensions.

Text values, NULL values and missing values in any or both pieces of a data-pair result in the entire data-pair being disregarded.