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. 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. Analyze data to identify design features or characteristics of the components of a proposed process or system to optimize it relative to criteria for success. Evaluate the impact of new data on a working explanation and/or model of a proposed process or system.Compare and contrast various types of data sets (e.g., self-generated, archival) to examine consistency of measurements and observations.Consider limitations of data analysis (e.g., measurement error, sample selection) when analyzing and interpreting data.Apply concepts of statistics and probability (including determining function fits to data, slope, intercept, and correlation coefficient for linear fits) to scientific and engineering questions and problems, using digital tools when feasible.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.Analyze data to define an optimal operational range for a proposed object, tool, process or system that best meets criteria for success.Īnalyzing 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 and interpret data to determine similarities and differences in findings.Consider limitations of data analysis (e.g., measurement error), and/or seek to improve precision and accuracy of data with better technological tools and methods (e.g., multiple trials). Apply concepts of statistics and probability (including mean, median, mode, and variability) to analyze and characterize data, using digital tools when feasible.Analyze and interpret data to provide evidence for phenomena.Distinguish between causal and correlational relationships in data.Use graphical displays (e.g., maps, charts, graphs, and/or tables) of large data sets to identify temporal and spatial relationships.Construct, analyze, and/or interpret graphical displays of data and/or large data sets to identify linear and nonlinear relationships.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.
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