After carrying out investigations, scientists and engineers must analyze and interpret data. Scientists analyze and interpret data to look for meaning that can serve as evidence. Often scientists seek to determine whether variables are related and how much they are related. Engineers use data to make decisions about designs, including whether a given design will work, the economic feasibility of a design, and potential alternatives. Raw data are organized and summarized using spreadsheets, databases, tables, graphs, and/or statistical analyses that help scientists interpret the data. Data can be either quantitative–using measurements–or qualitative–using descriptions. Ocean scientists and engineers use the full range of data organization and analysis tools available to scientists and engineers from all disciplines. For example, scientists on a ship may examine SONAR data collected in real-time to determine the shape of the seafloor (Fig 2.7 A). Biologists might graph the number of box jellyfish over time and compare these data to the phases of the moon to look for patterns (Fig 2.7 B). Research divers read and interpret data on dive tables to determine how long they can stay underwater (Fig 2.7 C).
Fig. 2.7. (A) Scientists aboard the National Oceanic and Atmospheric Association (NOAA) Ship Thomas Jefferson use computers to monitor and analyze SONAR data.
Image courtesy of National Oceanic and Atmosphere Association (NOAA) Ship Thomas Jefferson; Collection of Gretchen Imahori NOAA/NOS/OCS
Fig. 2.7. (B) Hawaiian box jellies have life cycles that coincide with lunar and tidal patterns.
Image courtesy of Openwaterpedia
Fig. 2.7. (C) A research diver plans a dive.
Image courtesy of National Oceanic and Atmosphere Association (NOAA) Flower Garden
The framework suggests that students should be able to analyze data systematically, use a variety of tools to organize and analyze data, recognize patterns and relationships in data, and draw conclusions from data. Students should have the opportunity to work with data both from classroom investigations and from large publicly available data sets. As students progress through school, students should record, display, analyze, and interpret increasingly more diverse and complex data. Students should also be able to differentiate between analyzing data for scientific purposes—to describe and relate variables, and engineering purposes—to improve a design or optimize a solution.
