Empirical Data Analysis and Error Evaluation

Formulate testable scientific questions and engineering problems while distinguishing hypotheses, theories, and scientific laws.

Plan and conduct controlled, comparative, and descriptive investigations adhering to rigorous laboratory safety practices.

Collect high-precision quantitative SI data and systematic qualitative observations using analog and digital laboratory instruments.

Process experimental data, construct linear and non-linear plots, calculate central tendencies, and quantify measurement uncertainty.

Develop, evaluate, and refine physical, conceptual, and mathematical models to explain systems and evaluate engineering designs.

Analyze datasets and secondary literature to identify causal relationships, isolate anomalies, and evaluate scientific claims.

Apply crosscutting concepts such as structure and function, conservation of mass and energy, and dynamic equilibrium to explain natural systems.

Construct evidence-based arguments using the Claims-Evidence-Reasoning framework, cite sources, and engage in peer review.

Evaluate the evolution of scientific knowledge over time, analyze ethical considerations in policy, and explore diverse STEM career pathways.