Calculate the standard error of the predicted y-value for each x in a regression.

`STEYX(known_y's, known_x's)`

- known_y's - an array or cell range
- known_x's - an array or cell range

`=STEYX(A3:A9,B3:B9)`

The STEYX function can be used to return the standard error of the predicted y-value for each x in the regression. This is useful for determining the accuracy of the regression line. The syntax for this function is above, where A3:A9 and B3:B9 are the x values and y values, respectively. This function can be used to determine the standard error of the predicted y-value for each x in the regression.

`=STEYX(A3:A9,B3:B9)`

The STEYX function can be used to calculate the standard error of the predicted y-value for each column in the regression. This is useful for determining the accuracy of the regression line. The syntax for this function is above, where A3:A9 and B3:B9 are the x values and y values, respectively. This function can be used to determine the standard error of the predicted y-value for each column in the regression.

The STEYX function calculates the standard error of the predicted y-value for each x in the regression. It requires known_y's and known_x's arguments which can be numbers, arrays, or references and must only contain numbers.

- The
**STEYX**function returns the standard error of the predicted y-value for each x in the regression model. - It takes two arguments which can be numbers, arrays, or references, but must contain only numbers.
- The function ignores empty cells, text, and logical values from arrays or references.

The STEYX function is a Sourcetable calculation used to determine the standard error of the predicted y-value for each x in a regression.

The standard error is a measure of the amount of error in the prediction of y for an individual x.

The STEYX function requires two arguments: known_y's and known_x's. These arguments can be numbers, arrays, or references.

The STEYX function ignores logical values, text representations of numbers, and empty cells.

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