In a negatively skewed distribution, which description correctly identifies the tail?

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Multiple Choice

In a negatively skewed distribution, which description correctly identifies the tail?

Explanation:
In a negatively skewed distribution, the left tail is longer and the bulk of the data cluster toward higher values on the right. That means there are a few unusually low scores pulling the tail down, while most observations lie at the higher end. So the description that the tail is to the left and the bulk is on the right matches the shape you’d expect. The other options describe different shapes: a tail to the right with bulk on the left is a positively skewed distribution; symmetry means tails are balanced on both sides; a uniform distribution has no concentrated peak or tail altogether.

In a negatively skewed distribution, the left tail is longer and the bulk of the data cluster toward higher values on the right. That means there are a few unusually low scores pulling the tail down, while most observations lie at the higher end. So the description that the tail is to the left and the bulk is on the right matches the shape you’d expect. The other options describe different shapes: a tail to the right with bulk on the left is a positively skewed distribution; symmetry means tails are balanced on both sides; a uniform distribution has no concentrated peak or tail altogether.

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