MS-P1.1: Ask questions that arise from careful observation of phenomena, models, or unexpected results, to clarify and/or seek additional information.

MS-P1.2: ask questions to identify and/or clarify evidence and/or the premise(s) of an argument.

MS-P1.6: Ask questions that can be investigated within the scope of the classroom, outdoor environment, and museums and other public facilities with available resources and, when appropriate, frame a hypothesis based on observations and scientific principles.

MS-P3.5: Collect data about the performance of a proposed object, tool, process or system under a range of conditions.

MS-P4.5: Apply concepts of statistics and probability (including mean, median, mode, and variability) to analyze and characterize data, using digital tools when feasible.

MS-P4.6: 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).

MS-P5.2: Use mathematical representations to describe and/or support scientific conclusions and design solutions

MS-P6.8: Optimize performance of a design by prioritizing criteria, making tradeoffs, testing, revising, and re- testing.

MS-P7.4: Make an oral or written argument that supports or refutes the advertised performance of a device, process, or system based on empirical evidence concerning whether or not the technology meets relevant criteria and constraints.

MS-P8.2: Integrate qualitative and/or quantitative scientific and/or technical information in written text with that contained in media and visual displays to clarify claims and findings.

HS-P1.6: Ask questions that can be investigated within the scope of the school laboratory, research facilities, or field (e.g., outdoor environment) with available resources and, when appropriate, frame a hypothesis based on a model or theory.

HS-P1.8: Define a design problem that involves the development of a process or system with interacting components and criteria and constraints that may include social, technical, and/or environmental considerations. 

HS-P3.6: Manipulate variables and collect data about a complex model of a proposed process or system to identify failure points or improve performance relative to criteria for success or other variables.

HS-P4.2: 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.

HS-P4.3: Consider limitations of data analysis (e.g., measurement error, sample selection) when analyzing and interpreting data

HS-P5.2: Use mathematical, computational, and/or algorithmic representations of phenomena or design solutions to describe and/or support claims and/or explanations.

HS-P6.5: Design, evaluate, and/or refine a solution to a complex real-world problem, based on scientific knowledge, student-generated sources of evidence, prioritized criteria, and tradeoff considerations.

HS-P7.5: Make and defend a claim based on evidence about the natural world or the effectiveness of a design solution that reflects scientific knowledge and student-generated evidence.

HS-P8.2: Compare, integrate and evaluate sources of information presented in different media or formats (e.g., visually, quantitatively) as well as in words in order to address a scientific question or solve a problem.