A data interpretation test asks you to read workplace charts, tables and dashboards, calculate from them, and judge what the data really shows. This guide explains what the test measures, works through a generic example of a misleading chart, summarises the research, and gives practical advice for candidates and employers.

What a data interpretation test measures

Dashboards and reports are now part of almost every job. The skill employers need is not just reading a figure off a chart but judging whether the chart tells the full story: whether the axis has been cut, whether a trend is real, whether two figures are comparable.

The Viewpoint Data Interpretation Test has 24 questions in 25 minutes, based on six workplace data sets, including charts, tables and dashboards, each with four questions. The questions test calculation and the judgement to spot a misleading chart. It is designed for roles that read data to make decisions, such as analysts, finance, operations and project roles, and graduates.

A worked example

The following is a generic illustration written for this article, not an item from the Viewpoint test.

A bar chart shows customer satisfaction scores for two branches. Branch A's bar looks about three times as tall as Branch B's. Looking at the axis, it starts at 80 rather than 0. Branch A scored 92 and Branch B scored 84.

Question: By how much did Branch A outscore Branch B, as a percentage of Branch B's score? The difference is 8 points; 8 ÷ 84 ≈ 9.5%. The bars suggest a huge gap, but the real difference is under 10%.

Question: Which statement is best supported? "Branch A's customers were much more satisfied" overstates it. "Branch A scored somewhat higher than Branch B" is supported. "Branch A has better staff" cannot be concluded from satisfaction scores alone.

The lesson is to check axes, units and what is actually being measured before drawing a conclusion.

What research says

The ways charts can mislead have been described for decades; Huff's classic book set out many of them, including truncated axes and selective comparisons [1]. Numerical and data reasoning tests are also among the ability measures that research has shown to predict job performance and training outcomes, including in UK studies [2]. A data interpretation test brings these together: objective evidence of how someone reasons with real-looking workplace data.

Using a data interpretation test well

For employers, the test is most useful where people make or influence decisions based on data. Read results in bands from Very Low to Very High, and look at speed and accuracy. At interview you might show a candidate a real chart from your organisation and ask what they would want to check before acting on it.

For candidates, read the title, axes and units of each chart before the question. Estimate before calculating, so you notice if an answer is wildly off. Use a calculator for the arithmetic and keep your attention on the reasoning.

See the Data Interpretation Test page, our guide to numerical reasoning, or all our ability tests.

Frequently asked questions

How long does the Viewpoint Data Interpretation Test take?

It has 24 questions across six data sets, with a time limit of 25 minutes.

What kinds of data are used?

Workplace charts, tables and dashboards.

How is it different from numerical reasoning?

Both involve working with data. Data interpretation puts more weight on judging what the data shows, including spotting misleading presentation.

Who is it designed for?

Analysts, finance, operations and project roles, graduates and other roles that use data to make decisions.

References

1. Huff, D. (1954). How to Lie with Statistics. New York: W. W. Norton.
2. Bertua, C., Anderson, N. & Salgado, J. F. (2005). The predictive validity of cognitive ability tests: a UK meta-analysis. Journal of Occupational and Organizational Psychology, 78(3), 387–409.