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Fisher's least significant difference (LSD) test is a modified $$t$$-test procedure utilized for post hoc comparisons after a significant one-way ANOVA result. Like other specialized techniques, its primary purpose is to evaluate differences between specific pairs of group means while mathematically controlling the compounded risk of making a Type I error (mistakenly rejecting a true null hypothesis) that occurs when conducting multiple standard $$t$$-tests.

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