Histogram shapes / Right-skewed
Right-Skewed Histogram (Positive Skew)
A right-skewed histogram has its peak on the left and a long tail stretching to the right. See a worked example, the mean vs median rule, and real cases like income and wait times.
What a right-skewed histogram looks like
A right-skewed histogram (also called positively skewed) piles up on the left and thins out toward the right. Most of the data sits at the low end, and a small number of large values pull a long tail out to the right side of the chart.
The example above is customer wait times in minutes. Most people wait a couple of minutes, but a handful wait much longer, and those long waits form the tail.
Mean, median, and mode
Skew changes the order of the three averages. In a right-skewed set the long right tail drags the mean upward, so:
mode < median < mean
The mode sits under the tall bars on the left, the median is in the middle, and the mean is pulled right by the outliers. If your mean is noticeably higher than your median, that gap is a quick sign the data leans right.
Where you see it
Income, house prices, wait times, response times, and file sizes are almost always right-skewed. There is a hard floor at zero and no ceiling, so the data can only stretch in one direction.
Paste your own numbers into the histogram maker and watch which side the tail falls on. If the mean prints higher than the median in the stats panel, you are looking at right skew.
Frequently asked questions
- Is a right-skewed histogram positive or negative skew?
- Positive. Right skew and positive skew mean the same thing: the long tail points to the right, toward the larger values, and the mean sits above the median.
- Why is the mean greater than the median in right-skewed data?
- The long right tail contains a few unusually large values. The mean uses every value, so those large numbers pull it upward, while the median only cares about the middle position and barely moves.