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How to Calculate and Get Range Values Between Datasets in Google Sheets

Getting the range of values between datasets in Google Sheets is an important analytics task. The range shows the span between the minimum and maximum values, giving you critical insights into the variability and distribution of your data.

In this comprehensive guide, I will show you multiple methods to calculate the range in Google Sheets using formulas and built-in functions. You’ll also learn how to compare ranges across multiple datasets.

What is Range in Google Sheets

In statistics, the range refers to the difference between the maximum and minimum values in a dataset. It shows the full scope or span of your data.

For example, if your data values are:

5, 10, 15, 20, 25

The minimum value is 5 and the maximum value is 25. So the range would be:

Range = Max value - Min value
Range = 25 - 5 = 20

So the range is 20.

Knowing the range gives you additional context into the distribution and variance of your data:

  • Smaller ranges indicate your data points are closer together and more consistent
  • Larger ranges means there’s more variability and spread across all your values

Why Calculate Range in Google Sheets

Here are some reasons getting the range in Sheets can be useful:

  • Quickly visualize how dispersed your data is
  • Identify any potential outliers that may skew ranges
  • Compare ranges across different datasets as a diagnostic metric
  • Track range over time to see changes in variability
  • Use ranges in calculations and modeling, like normalizing data

Getting the range alongside common statistical measures like mean and standard deviation provides a more complete picture into your underlying data.

How to Get Range of a Dataset

There are a few easy ways to get the range of values in Google Sheets.

Method 1: Use the MAX and MIN Functions

You can find the range using the MAX and MIN functions:

=MAX(range) - MIN(range)

Where range is your dataset.

For example:

=MAX(A1:A10) - MIN(A1:A10)

This returns the difference between the maximum and minimum values across the dataset in cells A1 to A10.

Pro Tip: You can also wrap this formula in ROUND() to get a rounded range for cleaner reporting.

Method 2: Use the IQR Function

Another method is using the interquartile range (IQR) function:

=IQR(range)

The interquartile range formula finds the range between the 25th and 75th percentile values. Many analysts prefer the IQR over the full range since it better handles outliers.

For example:

=IQR(B1:B15)

Returns the IQR across the dataset in B1 to B15.

Comparing Ranges Between Datasets

To compare ranges across multiple datasets:

  1. Calculate the range for each dataset using one of the methods above
  2. Display the ranges side by side
  3. Look at the relative size of each range

Larger ranges indicate more variability and dispersion across that particular dataset.

You can also calculate things like range differences or percentage changes between the datasets.

Here’s an example comparing ranges:

Range of Sales Dataset   = 20 
Range of Profit Dataset = 60

Here the range of the Profit dataset is much wider, suggesting higher volatility.

Visualizing Ranges in Google Sheets Charts

Simple column or bar charts are an easy way to visualize and compare ranges across different datasets:

  • X-axis = Dataset name
  • Y-axis = Range amount
  • One bar per dataset

This gives you a quick visual heatmap of the relative ranges across your data for better insights.

Limitations of Range

While easy to calculate, range has some statistical limitations to be aware of:

  • Sensitive to outliers that can skew range values
  • Doesn’t tell you about data distribution or shape
  • Can’t be used for more advanced analytics without normalization

Using range alongside other descriptive stats like variance, quartiles, histograms etc. provides a more complete perspective.

Conclusion

Finding the range in Google Sheets using the MAX and MIN functions is a simple way to understand the spread and variability of your data.

Comparing ranges across datasets allows you to quickly diagnose which ones have more consistency vs. volatility.

And visualizing using charts gives you an informative graphical heatmap into relative variability.

So while basic, incorporating range calculations into your Google Sheet analysis can surface helpful insights into your underlying data.

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