IQR Fence vs Outlier

The fences mark how far the data can reasonably reach before a value is worth flagging. You place the lower fence at $Q_1 - 1.5 \times \text{IQR}$ and the upper fence at $Q_3 + 1.5 \times \text{IQR}$, finding the quartiles by the median-excluded (TI-84) rule this site uses. If $Q_1 = 12$ and $Q_3 = 20$, then the IQR is 8, $1.5 \times 8 = 12$, and the fences sit at $12 - 12 = 0$ and $20 + 12 = 32$, so a value of 35 is an outlier by this rule while 31 is not. The fences are a convention for identifying points that deserve a second look, not proof that anything is wrong with those points.

An outlier is a point that stands apart from the overall pattern of the data. A common rule flags a value as an outlier when it falls below $Q_1 - 1.5 \times \text{IQR}$ or above $Q_3 + 1.5 \times \text{IQR}$, using the first quartile $Q_1$, the third quartile $Q_3$, and the interquartile range. For example, with $Q_1 = 3$, $Q_3 = 9$, and IQR $= 6$, any value below $3 - 9 = -6$ or above $9 + 9 = 18$ is an outlier. Outliers can be genuine extreme cases or data-entry errors, so you investigate before removing them.