What are the Assumptions Behind Normal Distribution?
For a dataset to be normally distributed, several assumptions must hold true:
Symmetry: The data should be symmetrically distributed around the mean. Unimodality: There should be a single peak in the distribution. No Outliers: Significant outliers can distort the normality of the data. Homogeneity of Variance: The variance should be consistent across the dataset.
