In Excel or Google Sheets, skewness for the sample data is =SKEW(C2:C31). It returns 2.19.
Skewness = n ÷ ((n − 1)(n − 2)) × Σ ((x − mean) ÷ sd)³
Step by step
- Download daily.csv below and open it in Excel (File → Open) or Google Sheets (File → Import). Columns: A day, B ad_spend, C website_orders, D app_orders, E avg_basket; data in rows 2 to 31.
- Click an empty cell and enter =SKEW(C2:C31).
- Check the result against 2.19. If it differs, check that the ranges cover rows 2 to 31 and that no cell holds text instead of a number.
The formula
=SKEW(C2:C31)Expected result on the sample data: 2.19.
What the result means
The single sale day gives this series a clear positive skew. Without it the daily orders are close to symmetric. That is typical: in business data a strong skew is often a handful of special days or customers, so find them before deciding the whole series is lopsided.
Notes for Excel
- Google Sheets supports the same function names. In locales that use a comma as the decimal separator, separate arguments with semicolons.
- Excel functions skip blank cells and text but include zeros. A missing day typed as 0 changes the answer; leave it blank if it is unknown.
Where skewness misleads
- Skewness is very sensitive to a few values; one outlier can create it.
- Excel SKEW, pandas .skew() and DuckDB skewness() use the same adjusted formula; SKEW.P and SciPy's default do not.
- With fewer than about 20 rows it is too noisy to read much into.
The plain-language explanation is on the Skewness page.
The data
| day | website_orders |
|---|---|
| 1 | 24 |
| 2 | 27 |
| 3 | 22 |
| 4 | 30 |
| 5 | 28 |
| 6 | 25 |
| 7 | 31 |
| 8 | 29 |
| 9 | 26 |
| 10 | 33 |
| 11 | 30 |
| 12 | 28 |
| 13 | 35 |
| 14 | 32 |
| 15 | 29 |
| 16 | 34 |
| 17 | 61 |
| 18 | 31 |
| 19 | 36 |
| 20 | 33 |
| 21 | 30 |
| 22 | 37 |
| 23 | 35 |
| 24 | 32 |
| 25 | 38 |
| 26 | 36 |
| 27 | 34 |
| 28 | 40 |
| 29 | 37 |
| 30 | 39 |
Same method, other tools
Related methods
Learn more about Excel
About the data on this page
The figures come from a small made-up dataset, printed above in full so you can check every number by hand. Download it as daily.csv. The results are computed from those rows when the page is built, and the Excel formulas, SQL and Python on these pages are run against the same rows before publishing, so the code and the answers agree.
To get these numbers from your own data without writing formulas, try AnalyzeIt: ask in plain words and it shows the working behind every figure.
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