Evidence, Data, and Models

Objective: Distinguish qualitative and quantitative data and interpret axes.

Qualitative data describe characteristics, while quantitative data report counts or measurements with units. A graph displays a relationship among variables; axis labels, units, scales, and legends must be read before interpreting a pattern. A trend may support a claim but does not alone identify a cause. Uncertainty and outliers should be examined rather than silently removed.

Objective: Support a claim using relevant evidence and explain the link.

A scientific claim is an answer to a question; evidence consists of observations or measurements relevant to it. Reasoning connects evidence to the claim using scientific principles and identifies alternative explanations or limitations. Strong arguments compare evidence quality and do not overstate what a small or biased dataset can establish. Contradictory evidence should be addressed rather than ignored.

Objective: Explain what a model represents and why scientists revise it.

A scientific model is a selective representation of a system used to describe, explain, or predict. Diagrams, equations, simulations, and physical objects can all be models. Their simplifications make some relationships clearer while leaving out detail, so their useful range must be stated. New evidence can lead to revisions of models and explanations; revision is part of scientific progress, not evidence that earlier observations never mattered.