The assumption of normality is a fundamental prerequisite in many statistical analyses, particularly parametric tests, which presumes that the data follows a normal distribution. Violations of this assumption can lead to inaccurate results, making it crucial to verify normality through tests or visual assessments before proceeding with analysis.