Continuous variables must possess normality in order to use parametric statistics
Normality and applied statistics
If a continuous variable's distribution yields skewness and kurtosis statistics below an absolute value of 2.0, then the assumption of normality has been met. More powerful parametric statistics can be used on continuous variables that meet the assumption of normality.
In certain instances, an ordinal variable can be upgraded to an interval scale of measurement if the assumption of normality is met for the ordinal distribution. This is especially true if the ordinal variable is a Likert-type score yielded from an empirically-validated instrument. More statistical power is achieved for these types of ordinal variables if the assumption of normality can be met and parametric statistics are used.
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