# How to Use the TRIMMEAN Function in Google Sheets : Quick & Easy Guide

In this tutorial you will learn How to Use the TRIMMEAN Function in Google Sheets.

The TRIMMEAN function in Google Sheets is a powerful tool for calculating the trimmed mean of a dataset.

The trimmed mean excludes a specific percentage of the highest and lowest values, providing a more robust measure of central tendency when outliers are present.

## Here’s a step-by-step guide on How to use the TRIMMEAN function in Google Sheets:

2. Enter the TRIMMEAN formula:

• In an empty cell where you want the trimmed mean to be displayed, type the following formula:
``````=TRIMMEAN(data_range, exclude_proportion)
``````

3. Replace the placeholders:

• `data_range`: Substitute this with the actual cell range of your data set. You can enter the range directly (e.g., A1:A10) or select the cells with your mouse.
• `exclude_proportion`: Enter the decimal value between 0 and 1 that represents the proportion of data points you want to exclude from each end (highest and lowest values) of the dataset.

Example:

Let’s say your data set is in cells A1:A10 and you want to calculate the trimmed mean by excluding the top and bottom 10% of the values.

In an empty cell (e.g., B11), enter the formula:

``````=TRIMMEAN(A1:A10, 0.1)
``````

4. Press Enter:

• Google Sheets will calculate the trimmed mean based on your specified parameters.

5. Understanding the results:

• The cell will display the trimmed mean of your data set, excluding the specified percentage of outliers from both ends.

Tips:

• Experiment with different `exclude_proportion` values to see how it affects the trimmed mean.
• The TRIMMEAN function is particularly useful for datasets with extreme values that might skew the standard mean.
• Consider using conditional formatting to highlight outliers in your data set for further analysis.

By following these steps, you can effectively utilize the TRIMMEAN function in Google Sheets to calculate a more accurate representation of the central tendency of your data when outliers are a concern.