Histogram shapes / Left-skewed
Left-Skewed Histogram (Negative Skew)
A left-skewed histogram peaks on the right with a long tail to the left. See a worked example, the mean vs median rule for negative skew, and common real-world cases.
What a left-skewed histogram looks like
A left-skewed histogram (also called negatively skewed) is the mirror image of a right-skewed one. The tall bars sit on the right, and a long tail trails off to the left where a few small values live.
The example above is exam scores. Most students score high, clustered near the top, while a small number of low scores stretch the tail toward the left.
Mean, median, and mode
With the tail on the left, the small outliers pull the mean down, so the order flips:
mean < median < mode
The mode is under the tall right-side bars, and the mean is dragged left by the low scores. When your mean prints lower than your median, the data leans left.
Where you see it
Test scores on an easy exam, age at retirement, and product ratings out of five all tend to skew left. There is a ceiling the data bunches against (a perfect score, a maximum rating) and only a few values fall well below it.
Drop your numbers into the histogram maker and check the stats panel. A mean below the median is the fingerprint of left skew.
Frequently asked questions
- Is a left-skewed histogram positive or negative skew?
- Negative. Left skew and negative skew are the same thing: the tail points to the left, toward the smaller values, and the mean sits below the median.
- What kind of data is usually left-skewed?
- Data with a natural ceiling that most values bunch against, like scores on an easy test, retirement ages, or five-star ratings where most reviews are 4s and 5s.