STEYX
TheSTEYX
function returns the standard error of the predicted yvalue for each x in the regression of the data set. It is commonly used in statistical analysis to evaluate the accuracy of a regression line. The function requires two arrays of data, one for the yvalues and one for the xvalues.
 How to use
STEYX
formula?  Examples of using
STEYX
formula STEYX
formula not working? Similar formulas to
STEYX
Usage
Use the STEYX
formula with the syntax shown below, it has 2 required parameters:
 data_y (required):
An array or range containing the dependent variable values.  data_x (required):
An array or range containing the independent variable values.
Examples
Here are a few example use cases that explain how to use theSTEYX
formula in Google Sheets.
Evaluating the accuracy of a regression line
By using the STEYX
function, you can determine how closely the predicted yvalues from a regression line match the actual yvalues of the data set.
Identifying outliers
Large standard errors of prediction (as calculated by STEYX
) for certain xvalues can indicate outliers in the data set.
Comparing regression models
By comparing the standard errors of prediction for different regression models, you can determine which model provides the most accurate predictions for a given data set.
Common Mistakes
STEYX
not working? Here are some common mistakes people make when using the STEYX
Google Sheets Formula:
Using incorrect data types for data_y and data_x
Make sure that the data_y and data_x parameters are arrays or ranges of numerical data.
Providing data in the wrong order
Make sure that the data_y parameter is the dependent variable and the data_x parameter is the independent variable.
Related Formulas
The following functions are similar to STEYX
or are often used with it in a formula:

STDEV.S
The
STDEV.S
formula calculates the standard deviation of a sample of data. It is commonly used to measure the amount of variation or dispersion of a set of values from their average. This formula accepts up to 255 arguments, which can be numbers, arrays, or references that contain numbers. The result is a measure of how spread out the data is, with a larger standard deviation indicating greater variability. 
SLOPE
The
SLOPE
formula calculates the slope of the linear regression line that best fits the input data. It is commonly used in statistics to analyze trends and predict future values based on past performance. 
INTERCEPT
The
INTERCEPT
function calculates the point where the line of best fit for a set of data intercepts the yaxis. This function is commonly used in regression analysis to find the constant b in the equation y=mx+b where m is the slope of the regression line.
Learn More
You can learn more about the STEYX
Google Sheets function on Google Support.