Which distribution shape is described as having a long tail extending to the right with most scores on the left?

Which distribution shape is described as having a long tail extending to the right with most scores on the left?

• A. Symmetrical
• B. Positively skewed
• C. Negatively skewed
• D. Normal

Answer: (B)

Skewness in a distribution shows which way data are pulled by outliers. When there’s a long tail on the right and most scores cluster on the left, the distribution is positively skewed. This happens because a few high values pull the tail toward higher numbers while the bulk of the data sits at lower values. In such a shape, the mean tends to be higher than the median, reflecting those high outliers. Other shapes don’t fit this description: a symmetrical distribution has tails that balance each other, a negatively skewed distribution has a longer tail on the left with most scores on the right, and a normal distribution is a perfectly symmetric bell curve.

Skewness in a distribution shows which way data are pulled by outliers. When there’s a long tail on the right and most scores cluster on the left, the distribution is positively skewed. This happens because a few high values pull the tail toward higher numbers while the bulk of the data sits at lower values. In such a shape, the mean tends to be higher than the median, reflecting those high outliers. Other shapes don’t fit this description: a symmetrical distribution has tails that balance each other, a negatively skewed distribution has a longer tail on the left with most scores on the right, and a normal distribution is a perfectly symmetric bell curve.