Use and share pictures, graphs, pictographs, and pie large data sets to identify linear order to make valid and reliable drawings, or writings of charts) to reveal patterns that and nonlinear relationships. scientific claims or determine an observations. indicate relationships. optimal design solution. Use graphical displays (e.g., Use observations (firsthand or Analyze and interpret data to maps, charts, graphs, and tables) Apply concepts of statistics and from media) to describe patterns make sense of phenomena, of large data sets to identify probability to scientific and or relationships in the natural and using logical reasoning, temporal and spatial engineering questions and designed worlds in order to mathematics, or computation. relationships. problems, using digital tools answer scientific questions and when feasible. Concepts should solve problems. include determining the fit of Compare and contrast data Distinguish between causal and functions, slope, and intercepts collected by different groups in correlational relationships in to data, along with correlation Compare predictions (based on order to discuss similarities and data. coefficients when the data is prior experiences) to what differences in their findings. linear. occurred (observable events). Analyze and interpret data to Analyze data to refine a problem provide evidence for Consider and address more Analyze data from tests of an statement or the design of a explanations of phenomena. sophisticated limitations of data object or tool to determine if the proposed object, tool, or process. analysis (e.g., sample selection) object or tool works as intended. Apply concepts of statistics and when analyzing and interpreting Use data to evaluate and refine probability (including mean, data. design solutions. median, mode, and variability) to analyze and characterize data, Compare and contrast various using digital tools when feasible. types of data sets (e.g., archival) to examine Consider limitations of data consistency of measurements analysis (e.g., measurement and observations. error), and seek to improve precision and accuracy of data Evaluate the impact of new data with better technological tools on a working explanation or and methods (e.g., multiple model of a proposed process or trials). system. Analyze and interpret data to Analyze data to optimize design determine similarities and features or characteristics of differences in findings. system components relative to criteria for success. Analyze data to define an optimal operational range for a proposed object, tool, process, or system that best meets criteria for success.
Use and share pictures, drawings, or writings of observations. Use observations (firsthand or from media) to describe patterns or relationships in the natural and designed worlds in order to answer scientific questions and solve problems. Compare predictions (based on prior experiences) to what occurred (observable events). Analyze data from tests of an object or tool to determine if the object or tool works as intended. graphs, pictographs, and pie charts) to reveal patterns that indicate relationships. Analyze and interpret data to make sense of phenomena, using logical reasoning, mathematics, or computation. Compare and contrast data collected by different groups in order to discuss similarities and differences in their findings. Analyze data to refine a problem statement or the design of a proposed object, tool, or process. Use data to evaluate and refine design solutions. large data sets to identify linear and nonlinear relationships. Use graphical displays (e.g., maps, charts, graphs, and tables) of large data sets to identify temporal and spatial relationships. Distinguish between causal and correlational relationships in data. Analyze and interpret data to provide evidence for explanations of phenomena. Apply concepts of statistics and probability (including mean, median, mode, and variability) to analyze and characterize data, using digital tools when feasible. Consider limitations of data analysis (e.g., measurement error), and seek to improve precision and accuracy of data with better technological tools and methods (e.g., multiple trials). Analyze and interpret data to determine similarities and differences in findings. Analyze data to define an optimal operational range for a proposed object, tool, process, or system that best meets criteria for success. order to make valid and reliable scientific claims or determine an optimal design solution. Apply concepts of statistics and probability to scientific and engineering questions and problems, using digital tools when feasible. Concepts should include determining the fit of functions, slope, and intercepts to data, along with correlation coefficients when the data is linear. Consider and address more sophisticated limitations of data analysis (e.g., sample selection) when analyzing and interpreting data. Compare and contrast various types of data sets (e.g., archival) to examine consistency of measurements and observations. Evaluate the impact of new data on a working explanation or model of a proposed process or system. Analyze data to optimize design features or characteristics of system components relative to criteria for success.
WI-Standards-for-Science-2017.docx