Free sampleVisualize and Analyze the Dataeasy
A pricing team needs a visual that reveals correlations and clusters between unit price and units sold across hundreds of SKUs. Which built-in visual matches the documented intent?
- AUse a stacked column chart with unit price as the legend across each SKU.
- BUse a scatter chart with unit price on one axis and units sold on the other. Correct
- CUse a donut chart with each SKU contributing a slice of the total.
- DUse a card visual showing the average of unit price across the SKU population.
Scatter charts are the documented choice for surfacing correlation between two numerical measures. Scatter charts plot data points at the intersection of two numerical values, revealing correlations and clusters. That is the documented use case for comparing price and volume across many SKUs.
Why A is wrong: Stacked columns compare category totals, not the intersection of two numerical measures across many points.
Why B is correct: Correct. Scatter charts plot data points at the intersection of two numerical values, revealing correlations and clusters.
Why C is wrong: Donut charts show part-to-whole composition for a small number of categories, not correlation.
Why D is wrong: Card visuals display a single fact and cannot reveal pairwise correlation or clustering between two measures.