Data Representation Passages

A Data Representation passage gives you almost no story. A short intro, then one to three figures: a table, a graph, maybe both. There's no mention of apparatus, trial groups, or steps someone followed, because the passage isn't testing whether you understand an experiment. It's testing whether you can pull exact values and trends out of a figure under time pressure. That's why it hands you graphs and stays quiet about collection: the data itself is the whole passage.

Because the passage is short on words, the ten to twelve questions attached to it all have to come from somewhere, and that somewhere is the two or three figures. Expect repeats: one question reads a single value off a table, the next asks how that value changes across a range, a third makes you combine two figures that share a variable. Read a figure in a fixed order every time: title first, so you know what it's actually showing. Then axes and units, so you don't mix up grams with milligrams or Celsius with Kelvin. Then the legend, if there is one, so you know which line or column is which. Only after all of that do you look for the trend, because a trend read before you know the units is a guess.

This is one of three passage formats, and it sits next to Research Summaries, which add a described procedure, and Conflicting Viewpoints, which drop the figures entirely in favor of competing arguments. Data Representation never asks about a control group or a trial design, because it never describes an experiment to begin with. If a second figure plots the same variable on a different scale, treat the two as separate readings and convert before you compare; don't assume the axes line up just because the variable name matches.