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My data is not normally distributed. Is the analysis ruined?

No. There are non-parametric alternatives for most common tests, transformations that are sometimes appropriate, and robust methods. Some tests are also more tolerant of non-normality than their reputation suggests, particularly at larger sample sizes. What matters is that you check, choose deliberately, and report what you did.

This comes up on Quantitative Data Analysis Support, where it is answered in the context of the work itself.

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