Data must be presented in a way that encourages exploration of potentially meaningful patterns and relationships. To provide insight into the meaning of data and its implications, scientists often use tabulating, graphing, or statistical analysis. Doing so provides evidence for interpretation of raw data.

Engineers typically utilize evidence-based decision making when designing a system, as opposed to trial and error. They gather an extensive amount of data on the design's performance, including under extreme conditions. By analyzing this data, they can make informed decisions on the design, predict or assess performance, and investigate failures. Additionally, this data helps engineers to define or clarify problems, discern economic feasibility, and evaluate alternatives (NRC Framework, 2012, p. 61-62).

As students progress, they should be able to employ a diversity of methods for tabulating, visualizing, and analyzing data including utilizing digital tools when possible. It is critical that they hone their abilities to recognize significant features and patterns, characterize the mathematical relationships between various variables, and assess sources of measurement error. As such, it is important that students have the tendencies to analysis data with purpose - so that they can exercise an effective demonstration using collected evidence as support for their conclusions.