1
Why Visualize Data?
Choose charts as analytical tools that reveal center, variability, shape, and relationships.
28 min3 outcomes
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Module 3
Choose, build, interpret, and critique visual displays for business and economic data, from dot plots and histograms to dashboards and deceptive graph repair.
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Visual Analyst
Lessons
15
Status
Available
Progress
0%
Choose charts as analytical tools that reveal center, variability, shape, and relationships.
Use stems and leaves to explore small numerical datasets while keeping original values visible.
Use individual-value displays to see center, spread, clustering, and unusual values.
Build frequency, relative-frequency, and cumulative-frequency tables from bins.
Use histograms as graphical frequency distributions and compare reasonable bin choices.
Label symmetric, skewed, multimodal, and unusual-value patterns without overstating them.
Use midpoints and cumulative percent to compare distribution shape and read percentile-style information.
Improve chart titles, labels, scales, gridlines, and clutter for a defined audience.
Use line charts for time series and explain arithmetic versus log-scale visual messages.
Compare categorical counts, sorted categories, cumulative percent, and stacked displays.
Use pie charts only for simple parts-of-a-whole situations and compare them with clearer bars.
Interpret paired observations, direction, strength, nonlinear patterns, trend lines, and correlation limits.
Use simple tables, cross-tabulations, rounding, and pivot-style summaries when exact values matter.
Detect nonzero origins, distorted aspect ratios, vague sources, 3D effects, and chart junk.
Build a short visual analytics report using histograms, line charts, bar or Pareto charts, scatter plots, tables, and critique.