The Step() is like Interpolate() except that it finds the corresponding y for a given x from a step-function fit rather than a linear fit. Use Step() with discrete y values (that is, when the y value’s corresponding x value can be only y1 or y2). However, when the y value’s corresponding x value can fall between y1 and y2, use Interpolate().

As with Interpolate, the data points can be specified as a list:

Step( x, x1, y1, x2, y2, ... );

or as matrices containing the x and y values:

Step( x, xmatrix, ymatrix );

Step( 35, [25 50 75 100], [5 10 15 25] );

If the discounts were on a sliding scale (in this example, between 5 and 10, you would use Interpolate():

Interpolate( 35, [25 50 75 100], [5 10 15 25] );

As with Interpolate(), the data points must create a positive slope.