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The phrase "non-normally distributed" is grammatically correct and usable in written English.
You can use this phrase whenever you are talking about data or samples that do not follow the usual pattern of most data being centered around the mean or average with the same level of frequency on either side of the mean. For example, you could say: "The data from this experiment was non-normally distributed, with the majority of results being higher than the mean."
Exact(60)
Non-normally distributed data have been normalized by logarithmic transformation.
Non-normally distributed data were analyzed by Mann-Whitney U-test.
Non-normally distributed data were log2 transformed and re-analyzed with the F-test.
Non-normally distributed data is indicated with ▼.
The calculated score was non-normally distributed.
Non-normally distributed data are presented as medians with interquartile range.
Non-normally distributed values were log-transformed before analysis.
Non-normally distributed variables were transformed (log or cubic transformation).
Non-normally distributed variables were logarithmically transformed, when necessary.
For non-normally distributed parameters, the Mann-Whitney U-test was utilized for comparisons.
Mean differences of non-normally distributed data were analyzed by the Mann-Whitney test.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com