# Normalization before sensitivity analysis

**URL:** <https://discourse.julialang.org/t/normalization-before-sensitivity-analysis/114484>\
**Category:** Modelling & Simulations\
**Tags:** globalsensitivityjl\
**Created:** [May 20, 2024, 8:39pm UTC](https://discourse.julialang.org/t/normalization-before-sensitivity-analysis/114484 "2024-05-20T20:39:39Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![duodenum](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/duodenum/32/36258_2.png) [@duodenum](https://discourse.julialang.org/u/duodenum)\
**Post date:** [May 20, 2024, 8:39pm UTC](https://discourse.julialang.org/t/normalization-before-sensitivity-analysis/114484/1 "2024-05-20T20:39:39Z")

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Hello,

I have a very general question: Is normalization necessary before global sensitivity analysis? Let’s say I have a differential equation that takes parameters x\_n. But parameters have widely different range of values they can take, let’s say x\_1 is a subset of [0,1] whereas x\_2 is a subset of [10, 1000]. Is some kind of normalization necessary? And if so, how can one implement this in GlobalSensitivity.jl?

Thanks,  
Yasir

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**Author:** ![juliohm](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/juliohm/32/215266_2.png) [@juliohm](https://discourse.julialang.org/u/juliohm)\
**Post date:** [May 20, 2024, 9:03pm UTC](https://discourse.julialang.org/t/normalization-before-sensitivity-analysis/114484/2 "2024-05-20T21:03:47Z")

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The answer is also very general: it depends on the method. For instance, some methods support categorical variables for which normalization doesn’t make much sense.

I will let the maintainers of GlobalSensitivity.jl discuss the specific methods implemented and their requirements.

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**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [May 20, 2024, 9:57pm UTC](https://discourse.julialang.org/t/normalization-before-sensitivity-analysis/114484/3 "2024-05-20T21:57:09Z")

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Kind of depends on the method, though it’s all already re-scaled to the output variable. It basically calculates the variance explained over a parameter space. The percentage of the variance explained in the output with respect to input x does not really care about the relative size of the space of x, just how much y varies as you change x. Internally, many of the methods re-scale down to a [0,1]^n grid internally anyways.