# Ways to test the validity/usefulness/salience of your data

**URL:** <https://discourse.flucoma.org/t/ways-to-test-the-validity-usefulness-salience-of-your-data/841>\
**Category:** Pre-Release Toolbox2 Usage\
**Created:** [March 18, 2021, 6:16pm UTC](https://discourse.flucoma.org/t/ways-to-test-the-validity-usefulness-salience-of-your-data/841 "2021-03-18T18:16:18Z")\
**Posts on this page:** 1\
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**Author:** ![tremblap](https://discourse.flucoma.org/user_avatar/discourse.flucoma.org/tremblap/32/5_2.png) [@tremblap](https://discourse.flucoma.org/u/tremblap)\
**Post date:** [March 2, 2022, 5:46pm UTC](https://discourse.flucoma.org/t/ways-to-test-the-validity-usefulness-salience-of-your-data/841/38 "2022-03-02T17:46:26Z")

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> [@tedmoore](#):
>
> If you _know_ that you have some crazy outliers, Robust Scaler might be a better choice as it will keep you in the centred at 0 with a spread of 1 vicinity.

actually, if you know you have multimode data, and not standard, Robust Scaler should be at least as good if not better. The Khan Academy video I posted long ago showed that very beautifully.

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