For AI agents: use /llms.txt for the Nakafa content index.
We know the three main measures of central tendency: Mean (average), Median (middle value), and Mode (most frequent value). All three tell us about the "center" or tendency of the data, but they have different properties and are suitable for different situations.
Choosing the wrong measure can give a misleading picture of the data. So, let's understand when it's best to use each measure.
Here's a concise guide on when to use each measure:
| Measure | Best Data Type | Outlier Influence | When to Use? |
|---|---|---|---|
| Mean | Quantitative (Numbers) | Highly Influenced | When data has no significant outliers & you want a representation involving all data values. |
| Median | Quantitative (Numbers) | Not Influenced | When data has outliers or the distribution is skewed (not symmetrical). Provides a stable middle value. |
| Mode | Qualitative & Quantitative | Not Influenced | When you want to know the most popular value/category or the most frequent occurrence. |
Example Scenarios:
