The assumptions of normality refer to the expectation that data in a statistical analysis follow a normal distribution, which is a symmetric, bell-shaped curve. This assumption is crucial in many parametric statistical tests, as it underpins the validity of inferences made about population parameters based on sample data. When data do not meet this assumption, it can lead to inaccurate conclusions and necessitate the use of alternative methods.
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