Which visualization technique is effective in highlighting data points that stand out in a dataset?

The most effective visualization technique for highlighting data points that stand out in a dataset is to add an outlier visualization. Outliers are observations that deviate significantly from other data points in a dataset. By specifically visualizing outliers, one can easily identify these unusual values, helping to draw attention to them in analysis.

Outlier visualizations can often include markers or distinct colors that differentiate these data points from the rest, making them immediately noticeable on the graph. This focused approach allows analysts and stakeholders to grasp the significance of these data points in the context of the overall dataset, such as understanding potential anomalies or insights that would not be apparent through other visualization methods.

Other techniques like box plots are useful for displaying the distribution and can help identify outliers as part of a broader context, but they do not directly emphasize individual outliers in the same way. Similarly, bar graphs can show variations in categorical data but might not effectively convey individual data point anomalies. Modifying trend lines can offer insights into overall trends but does not specifically address the need to highlight standout data points. Hence, using an outlier visualization provides the clearest method for bringing attention to those exceptional values.