Check out the linest_m function to calculate the slope of your linear regression:
From the HELP:
linest_m ([{set_expression}][ distinct ] [total [<fld {,fld}>] ]y-expression, x-expression[, y0 [, x0 ]])
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 in x-expression and y-expression iterated over the chart dimension(s). Text values, null values and missing values in any or both pieces of a data-pair will result in the entire data-pair to be disregarded.
An optional valye 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.
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.
This function has the same limitations for nested aggregation as the avg([{set_expression}] [ distinct ] [ total [<fld { , fld } >]] expression) function. The linest_m function supports Set Analysis and the total qualifier in the same way as the avg([{set_expression}] [ distinct ] [ total [<fld { , fld } >]] expression) function.
Examples:
linest_m( Y, X )
linest_m( A/B, X*Y/3 )
linest_m( total Y, X )
linest_m( total <Z> Y, X)
linest_m( Y, X, 0 )
linest_m( Y, X, 1, 1 )
