> For the complete documentation index, see [llms.txt](https://docs.predicteasy.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.predicteasy.com/data-preprocessing/standard-scaling.md).
# Standard Scaling
Standard scaling (or standardization) rescales numeric data to have a mean of 0 and a standard deviation of 1. It's especially useful for algorithms that assume features are centered around zero and have a uniform variance. This scaling method doesn't have specific upper and lower bounds, but it transforms data to have a mean of 0 and unit variance.
Steps to follow:
1. Identify and highlight the columns you wish to standardize. Click and drag to select the specific range (e.g., A1:A30).
2. Look for the "Standard scale" option within PredictEasy and select specific range.
3. If the selected area has headers, make sure to check the checkbox designated for headers. This ensures that the add-on considers the first row as header during the Standard scalar process.
4. Click the "scale" button within the PredictEasy interface. This action triggers the standardization process.
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