How to Find Skewness in Excel: Quick Function Method for Data Analysis

Skewness reveals data asymmetry in seconds, not hours. I first used this in a Carnegie Mellon stats class to spot outliers in test scores.

Excel’s built-in SKEW and SKEW.P functions handle the math—no manual calculations. Just select your dataset and let the formula do the work. The result tells you if your data leans left, right, or stays balanced.

You’ll get a clear measure of distribution shape with one formula. Positive values mean a long right tail; negative values indicate a left tail. Zero means perfect symmetry.

Works for any dataset, from sales figures to survey responses. Here’s how to interpret the numbers.

What Youll Need

Instructions

Here’s the procedure I follow to get accurate results without unnecessary complexity.

Select the range of cells containing your data. I always ensure there are no blank cells or text values in the selection, as these will cause the function to return a #DIV/0! error. If your data has headers, exclude them from the selection.

Verify the range by checking the formula bar—it should display something like A1:A20 for a single column. For multiple columns, use a rectangular range like A1:C20. This ensures the function analyzes the correct dataset.

In an empty cell, type =SKEW( and then select your data range. Close the parentheses and press Enter. The function will return a positive value if the distribution is skewed right, negative for left skew, or near zero for symmetry.

For example, =SKEW(A1:A20) calculates skewness for the first twenty cells in column A. If you need to reference a non-contiguous range, separate ranges with commas, like =SKEW(A1:A10, C1:C10).

A result of 0 indicates a perfectly symmetrical distribution. Positive values (e.g., 1.2) mean the tail on the right side is longer or fatter, while negative values (e.g., -0.8) indicate a left skew.

I like to compare this value against the standard error of skewness, which is SQRT(6_N_(N-1)/((N-2)(N+1)(N+3))) where N is the sample size. If the skewness is more than twice the standard error, the data is significantly skewed.

Create a histogram to visually confirm the skewness. Select your data, go to Insert > Charts > Histogram. The shape of the bars will show whether the tail is on the left or right, matching your SKEW function result.

If the histogram looks symmetrical but the SKEW function returns a non-zero value, check for outliers. A single extreme value can disproportionately affect skewness, even in an otherwise balanced dataset.

If your dataset has fewer than 3 values, the SKEW function will return a #DIV/0! error. This is expected, as skewness requires at least three points to measure asymmetry. For small datasets, consider using the SKEW.P function, which treats the data as a population.

For large datasets, performance matters. If you notice Excel slowing down, break the data into smaller ranges and calculate skewness for each subset separately. This approach maintains accuracy while improving responsiveness.

Tips and Common Mistakes

These refined techniques will help you get the most accurate skewness results while avoiding common pitfalls.

Data Cleanup First: In Step 1, I learned the hard way that even one text value or blank cell in your range will trigger that dreaded #DIV/0! error. Use Excel’s Go To Special feature to quickly identify and remove any non-numeric entries before proceeding. This single step saves more time than any shortcut I know.

Range Verification Trick: For Step 2, after selecting your range, glance at the formula bar to confirm it matches what you intended. I’ve seen colleagues accidentally include header rows or entire columns, which completely throws off the calculation. The example =SKEW(A1:A20) works perfectly when you’ve got exactly 20 data points with no headers.

Outlier Awareness: Step 4’s histogram visualization is your best friend for spotting anomalies. I once spent hours troubleshooting why my skewness value didn’t match the visual distribution—turned out a single outlier was distorting everything. Always cross-check your numerical result with the histogram’s shape.

Small Dataset Solution: When working with fewer than 3 values as mentioned in Step 5, don’t waste time trying to force the SKEW function to work. Switch to SKEW.P immediately—it’s designed specifically for small populations and will give you valid results where the standard function fails.

Frequently Asked Questions

Now you know how to calculate skewness in Excel using simple functions! Understanding data distribution is key to better analysis, and you’re now equipped to do just that. 🎯 Try applying these steps to your own datasets and explore how skewness impacts your insights.