Data Interpretation

Overview

Data interpretation measures how quickly and accurately you can extract figures from a visual and reason with them — reading the right mark, then applying totals, differences, averages, proportions and percentage change under time pressure. Each item is a freshly generated bar chart, line graph, pie chart or table of business data with a single question attached. As used by cut-e (Aon) in its 'scales numerical' test and by SHL's Verify Numerical Reasoning and comparable batteries, the two answer formats mirror the real thing: numerical multiple-choice (SHL) and True / False / Cannot Say statements (cut-e), where 'Cannot Say' is the correct response whenever the data shown does not settle the question. Because each real test keeps a single format throughout, you choose one per run — all numeric, all True/False/Cannot Say, or a practice mix. The data source is a choice too, and an honest one: by default each question shows a single, pre-scoped chart — a deliberate simplification that isolates the reading and arithmetic. The real cut-e test instead splits one company's data across several tabbed datasets, and locating the figure the statement names is part of what is timed; the Tabbed workbook option reproduces exactly that, presenting 4–6 related company datasets as tabs with each question naming the metric you must find (with a little extra time per item to budget for the search). Then pick a Progression Test (10, 20 or 30 items) to measure yourself against a target, or an Open Challenge (5, 10 or 15 minutes) to score as many as you can against the clock.

Assessments

Could show up in cut-e / Aon and SHL-based selections.

Airline mappings are based on public information and may change.

Example: read the chart, then answer

Each item gives you a chart or table and one question about it. Find the values it asks for, do the arithmetic, and pick the matching answer. Here: how much higher was Q4 revenue than Q2?