Nature of Science
The Nature of Science domain tests how physics knowledge is constructed and checked: experimental design, measurement quality, uncertainty, data representation, and the roles of models, laws, and theories.
Experimental design and measurement
A controlled experiment changes one independent variable while holding others constant and measures a dependent variable. A control group or baseline supports causal claims. Accuracy is closeness to the accepted value; precision is reproducibility. Random error scatters repeated measurements and can be reduced by averaging; systematic error shifts all readings in one direction and is not fixed by averaging.
Units, figures, and uncertainty
Convert to SI units before calculating. Check dimensional consistency. Report significant figures consistent with measurement precision; in multiplication and division, keep the least number of significant figures. Fractional uncertainties add approximately when quantities are multiplied or divided.
Worked example
A metal sample has mass 24.6 ± 0.1 g and volume 9.0 ± 0.3 cm³. Density is 24.6/9.0 = 2.733 g/cm³. Fractional uncertainty is 0.1/24.6 + 0.3/9.0 ≈ 0.0041 + 0.0333 = 0.0374, or 3.7%. Absolute uncertainty is 0.0374 × 2.733 ≈ 0.10 g/cm³. Report 2.73 ± 0.10 g/cm³, which correctly shows the volume measurement limits precision.
Traps that cost marks
Do not call a reproducible but offset measurement “accurate.” Do not treat a scientific law as a proven theory or a theory as a guess. Avoid dropping units mid-calculation, over-reporting calculator digits, and claiming a graph “proves” a hypothesis rather than supports it. Distinguish correlation from causation.