To emphasize the most critical data points in a scatter plot while still showing the full dataset, what visual element can an analyst adjust for less important points?

The visual element an analyst can adjust for less important points is their opacity. Opacity, also known as transparency, describes the degree to which a graphical element, such as a data point marker in a scatter plot, is permeable to light, ranging from completely solid (fully opaque) to entirely see-through (fully transparent). A scatter plot displays individual data points, each representing an observation. To emphasize critical data points while retaining the complete dataset visibility, an analyst reduces the opacity of the less important points. This adjustment makes those points appear semi-transparent and less visually dominant, allowing them to fade into the background while still being present and contributing to the perceived overall data distribution or density. Critical data points can then be highlighted by maintaining their full opacity, or by employing distinct visual attributes like a different color or larger size, ensuring they stand out clearly against the more translucent less important points. This method allows the viewer to focus on key insights without losing the contextual understanding of the entire dataset.