The PERCENTRANK.INC function in Google Sheets is a powerful tool used to determine the relative standing of a value within a dataset. This function provides a measure of how a particular value compares against a range of numbers, yielding results that can be useful in statistical analysis or data interpretation. The output, which ranges from 0 to 1, indicates the percentage of data points that fall below the specified value.

Syntax

PERCENTRANK.INC(data, value, [significance])

• data: The range or array of numbers representing the dataset you wish to evaluate.
• value: The specific number whose percentage rank you want to determine within the dataset.
• significance: (Optional) Specifies the number of significant digits for the returned percentage rank. If omitted, the default is 3 significant digits.

Example #1

PERCENTRANK.INC(A1:A10, 50)

This function determines the percentage rank of the value 50 within the dataset in cells A1 to A10. For example, if 50 is greater than 70% of the values in this range, the result would be 0.7.

Example #2

PERCENTRANK.INC(B1:B5, 3, 2)

This computes the percentage rank of the number 3 in the dataset from B1 to B5, returning the result with two significant digits. If 3 is the lowest number, for instance, the output could be 0.00.

Example #3

PERCENTRANK.INC(C1:C20, 82, 1)

Here, the function checks the percentage rank of 82 within the range C1 to C20, outputting the result rounded to one significant digit. If 82 is higher than 75% of the values, the output would be 0.8.

Error handling

• NUM!: Occurs when the specified value is less than the smallest number or greater than the largest number in the dataset.
• DIV/0!: Happens when the dataset is empty, meaning there are no values to compare against.
• VALUE!: Indicates that the data provided is not in a recognized format or type for the function.

Conclusion

The PERCENTRANK.INC function is a valuable asset in statistical analysis, helping users understand data distributions by providing insights into the relative positions of individual values. This function can facilitate data-driven decisions and improve the interpretation of numerical datasets by presenting information in a comprehensible percentile format.