The visualization of the vectors in the score matrix, T, is usually referred to as a score plot. The most common score plot is the 2D score scatter plot, where two vectors of scores are plotted against each other. The plot can be seen as a 2D window into the multidimensional space. Here, it is possible to identify classes of observations that share similar properties and are separated to different areas of the plot. It is also possible to identify outliers, anomalous observations that lie far from the others.

The 3D score scatter plot uses three vectors of scores instead of two and can sometimes facilitate the viewing when observations are separated in more than two dimensions.

The 1D score series plot can be useful when observations are in chronological order, e.g. when there is some kind of process data. It may be possible to follow observation fluctuations within this type of plot.