STEYX: Google Sheets Formulae Explained

In this comprehensive guide, let’s delve into the STEYX formula in Google Sheets. The STEYX formula is a potent statistical function that calculates the standard error of the predicted y-values for each x-value in a linear regression. Understanding the accuracy of your linear regression model and making better predictions based on your data becomes easier with this formula. We will cover the syntax, examples, tips and tricks, common mistakes, troubleshooting, and related formulae for the STEYX function.

STEYX Syntax

The syntax for the STEYX formula in Google Sheets is as follows:

=STEYX(known_y's, known_x's)

Where:

• known_y’s – This refers to a range or array encompassing the known y-values in your dataset.
• known_x’s – This refers to a range or array encompassing the known x-values in your dataset.

Please note that both arguments must have the same size and contain numeric values. The STEYX function will then return the standard error of the predicted y-values for each x-value in the linear regression.

STEYX Examples

Now, let’s explore some examples showcasing the usage of the STEYX formula in Google Sheets.

Example 1: Basic Usage

Imagine you have a dataset with the following x and y values:

X: 1, 2, 3, 4, 5
Y: 2, 4, 5, 8, 10

To calculate the standard error of the predicted y-values, apply the following formula:

=STEYX(B2:B6, A2:A6)

This will provide you with the standard error of the predicted y-values for the given x-values in the linear regression.

Example 2: Using STEYX with Non-Numeric Data

If your dataset contains non-numeric data, the STEYX function will result in a #VALUE! error. To avoid this, apply the IF and ISNUMBER functions to filter out non-numeric data. For instance, if your dataset contains the following values:

X: 1, 2, "A", 4, 5
Y: 2, 4, "B", 8, 10

Use the following formula to calculate the standard error of the predicted y-values:

=STEYX(IF(ISNUMBER(B2:B6), B2:B6, ""), IF(ISNUMBER(A2:A6), A2:A6, ""))

STEYX Tips & Tricks

To help you make the most out of the STEYX formula in Google Sheets, here are some useful tips and tricks:

1. Ensure that the ranges for your known_y’s and known_x’s arguments possess the same size. If they don’t, using the STEYX function will result in a #N/A error.
2. Use the FILTER function to eliminate non-numeric data from your dataset before utilizing the STEYX function. This will prevent #VALUE! errors.
3. Combine the STEYX function with other statistical functions such as SLOPE, INTERCEPT, and RSQ. This will enable you to gain a more profound comprehension of your linear regression model.

Common Mistakes When Using STEYX

Here are some common mistakes to steer clear of when employing the STEYX formula in Google Sheets:

1. Using non-numeric data in your known_y’s and known_x’s ranges. This will generate a #VALUE! error.
2. Utilizing ranges of different sizes for your known_y’s and known_x’s. This will result in a #N/A error.
3. Failing to employ the appropriate functions such as IF, ISNUMBER, or FILTER to eliminate non-numeric data.

Why Isn’t My STEYX Working?

If your STEYX formula fails to produce the desired results in Google Sheets, consider the following troubleshooting steps:

1. Check for non-numeric data in your known_y’s and known_x’s ranges. Ensure you use the appropriate functions such as IF, ISNUMBER, or FILTER to eliminate non-numeric data.
2. Verify that your known_y’s and known_x’s ranges have the same size. If they differ in size, the STEYX function will result in a #N/A error.
3. Double-check the syntax of your STEYX formula to ensure it is entered correctly.

STEYX: Related Formulae

Here are some additional formulae that can prove useful when working with the STEYX function in Google Sheets:

1. SLOPE – Calculates the slope of the linear regression line for a dataset.
2. INTERCEPT – Determines the y-intercept of the linear regression line for a dataset.
3. RSQ – Calculates the coefficient of determination (R-squared) for a linear regression model.
4. FORECAST – Predicts a future y-value based on the linear regression model for a given x-value.
5. LINEST – Returns an array of statistics pertaining to a linear regression model, including slope, intercept, and standard errors.

By mastering the STEYX formula and its related functions, you can develop a deeper understanding of your linear regression models and make more accurate predictions based on your data in Google Sheets.

Mr Reviews