The MODE.MULT function in Google Sheets is a powerful tool designed to return the most common values from a data set. This function is particularly useful when analyzing large sets of numbers where you want to find frequent occurrences, such as responses in surveys or numerical data in financial reports. Rather than just a single most frequent value, MODE.MULT can return multiple values, offering a comprehensive view of the data distribution.

Syntax

MODE.MULT(value1, [value2, ...])

• value1: The first range of data or array from which you want to extract the mode.
• value2: (Optional) Additional ranges or arrays to include. You can add multiple optional ranges separated by commas.

Example #1

=MODE.MULT(A1:A10)

This function identifies the most commonly occurring values in the range A1 to A10. For instance, if the range contains values {1, 2, 3, 1, 3, 1, 4}, the result would be {1}, as it appears most frequently.

Example #2

=MODE.MULT(B1:B20, C1:C20)

This formula examines two separate ranges, B1 to B20 and C1 to C20, returning any modes present in either location. If these ranges yield values {4, 5, 5, 6} and {5, 7, 8}, it will return {5} since it’s the most frequent value across both arrays.

Example #3

=MODE.MULT(D1:D15, E1:E15, F1:F15)

This function will analyze three different ranges; D1 to D15, E1 to E15, and F1 to F15. If these contain the numbers {10, 10, 20, 30}, {5, 10, 15}, and {10}, it will yield {10}, showcasing it as a repeating mode in the combined dataset.

Error handling

• N/A: Indicates that no mode exists in the dataset. This can occur when all values are unique or when there are no entries.
• VALUE!: This error appears if non-numeric data is included in the referenced ranges, as MODE.MULT can only process numerical values.
• REF!: Indicates that a referenced cell is invalid, possibly due to deleted or moved ranges or incompatible reference types.

Conclusion

The MODE.MULT function is invaluable for anyone looking to analyze data effectively. Its ability to return all most frequently occurring values in a dataset allows for richer data interpretation. Understanding how to use this function can help in making informed decisions based on reliable data insights.