Using MY NASA DATA to Teach: Science and Engineering Practice:

4. Analyzing and Interpreting Data


Once collected, data must be presented in a form that can reveal any patterns and relationships and that allows results to be communicated to others. Because raw data as such have little meaning, a major practice of scientists is to organize and interpret data through tabulating, graphing, or statistical analysis. Such analysis can bring out the meaning of data – and their relevance – so that they may be used as evidence. (NRC Framework, 2012, p 61-62)

K-2: Analyzing data in K-2 builds on prior experiences and progresses to collecting, recording, and sharing observations.

  • Use observations (firsthand or from media) to describe patterns in the natural world in order to answer scientific questions. (K-ESS2-1) (1-ESS1-1)

3-5: Analyzing data in 3-5 builds on K-2 experiences and progresses to introducing quantitative approaches to collecting data and conducting multiple trials of qualitative observations. When possible and feasible, digital tools should be used.

  • Represent data in tables and various graphical displays (bar graphs and pictographs) to reveal patterns that indicate relationships. (3-ESS2-1)(5-ESS1-2)
  • Analyze and interpret data to make sense of phenomena using logical reasoning. (4-ESS2-2)

6-8: Analyzing data in 6-8 builds on K-5 experiences and progresses to extending quantitative analysis to investigations, distinguishing between correlation and causation, and basic statistical techniques of data and error analysis.

  • Analyze and interpret data to determine similarities and differences in findings. (MS-ESS1-3)(MS-ESS3-2)
  • Analyze and interpret data to provide evidence for phenomena. (MS-ESS2-3)

9-12: Analyzing data in 9-12 builds on K-8 experiences and progresses to introducing more detailed statistical analysis, the comparison of data sets for consistency, and the use of models to generate and analyze data.

  • Analyze data using tools, technologies, and/or models (e.g., computational, mathematical) in order to make valid and reliable scientific claims or determine an optimal design solution. (HS-ESS2-2) (HS-ESS3-5)