AI did not end the data literacy crisis. It changed it. As machines move from providing information to interpreting it and recommending what to do, the scarce skill is becoming judgment: knowing what to trust, what to question, and what decisions are still ours to make.
Evidence does not make decisions. People interpret it, weigh it, challenge it, and make judgments. A courtroom reveals what leaders can learn about evidence, expertise, confidence, and data-informed decision-making.
Feeling sure doesn't mean you're right. Learn five simple ways to question what feels true, spot what might be influencing you, and make better decisions about what to believe.
Match the right visualization to your question, your data types, and the story you need to tell. Filter by question type or variable type, or search by name.
The Five Question Types
Before picking a chart, identify what question your chart needs to answer. Five categories cover almost every situation a non-analyst encounters. Each category has sub-types that narrow the fit.
This guide is the deep-dive companion to the Integrated Data Visualization Framework. The framework teaches the full workflow for working with data. This guide picks up at the chart-selection step, with specific chart examples and trade-offs for each question type.
Type 1
Comparison
"How do values differ across categories or groups?"
Simple magnitudeHow do these groups stack up on one measure?
RankingWho is on top? Who is at the bottom?
DeviationHow far above or below baseline?
Paired comparisonHow does each entity compare on two related values?
Timeline comparisonHow do durations or time spans compare?
Type 2
Trend
"How does a value change over time?"
Simple trendWhat is the overall direction of change?
Change between two pointsWhat was the difference from time A to time B?
Ranking over timeHow did positions change over the period?
Faceted trendWhat is the trend within each unit, shown separately?
Type 3
Composition
"What parts make up a whole?"
Static part-to-wholeAt this moment, what percentage is each piece?
Composition across groupsHow does the mix differ across entities or time?
Sequential processAt each stage, how much remains or moves where?
Pareto compositionWhich few items drive most of the total?
Type 4
Distribution
"How are values spread out?"
Shape of distributionWhere do most values cluster, how are they dispersed?
Range and variabilityWhat is the min, max, and variation?
Type 5
Relationship
"How do two or more variables move together?"
CorrelationDo two continuous variables move together?
Multi-dimensional patternHow do values vary across two categorical dimensions?
Parallel trendsDo two metrics over time move together or diverge?
