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Excel STEYX Function

Author: Amanda Li Last Modified: 2022-08-05

The STEYX function returns the standard error of the predicted y value for each x in a linear regression given by a series of coordinates represented by paired numbers.

steyx function 1


Syntax

=STEYX(known_ys, known_xs)


Arguments

  • known_ys (required): An array or range of dependent variables.
  • known_xs (required): An array or range of independent variables.

Return Value

The STEYX function returns a numeric value.


Function Notes

  • Arguments can be either of the following:
    • Numbers;
    • Names, arrays, or references that contain numbers.
  • Logical values and other values that can be converted to numbers that you type directly into the list of arguments will be counted.
  • If text or empty cells are referenced as either of the arguments, the values will be ignored.
  • STEYX returns the #N/A error if known_ys and known_xs have different numbers of data points.
  • STEYX returns the #DIV/0! error if known_ys and known_xs are empty or have less than three data points.
  • The equation for the standard error of the predicted y value is:

    Where x and y are the sample means of the two arrays of values, and n is the sample size.

Example

Take the table below as an example. To get the standard error of the predicted y-value for each x in the regression, please copy or enter the formula below in the result cell, and press Enter to get the result.

=STEYX(B6:B12,C6:C12)

steyx function 2


Related functions

Excel SLOPE Function

The SLOPE function returns the slope of a regression line based on the supplied y values and x values. The slope is the ratio of rise and run, which means the vertical distance divided by the horizontal distance between any two points on the line.

Excel INTERCEPT Function

The INTERCEPT function calculates the point at which a linear regression line will intersect the y-axis by using the given x-values and y-values.

Excel FORECAST Function

The FORECAST function predicts a future value based on existing values by using the linear regression.


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