Reading the Axes, Units and Labels First

Every data question hides its trap in the axis labels, not the bars or dots. Before looking at the choices, spend ten seconds naming what each axis counts, what unit it uses, and where its scale starts and ends. A vertical axis labelled grams per square metre is a density, not a total. A vertical axis that starts at 40 instead of 0 is truncated, so bar heights show the amount above 40, not the whole quantity, and ratios between bars get exaggerated. A legend tells you which line or bar belongs to which series, which matters the moment a graphic carries two series but the claim only names one of them.

Tables add a second habit: check what a row or column actually represents before trusting a sum. Percentage columns sometimes don't add to 100 because of rounding, not because of an error, so don't flag that as a problem to explain, and don't force a correction the data doesn't need. When a claim names a specific category, like one islet or one district, the matching evidence has to come from that same category, not an average across all of them.

This habit connects to the same section's inference and evidence questions: once you've read the axes correctly, you're ready to ask whether a choice matches the actual quantity measured, or whether it quietly swaps in a total for a rate, or a truncated comparison for a real one. Getting the labels right first turns a data question into simple matching instead of a guessing game.