Foundations of Scientific Inquiry and the Nature of Science
This domain tests how scientific knowledge is built and tested: experimental design, measurement, data interpretation, models, and the distinctions among hypothesis, theory, and law. Questions often ask you to identify variables, judge whether evidence supports a claim, or apply significant-figure rules.
Core rules and concepts
- The independent variable is manipulated; the dependent variable is measured; controlled variables are held constant to prevent confounding.
- Replication, random assignment, and appropriate sample size improve reliability; a control group isolates the treatment effect.
- Accuracy is closeness to the true value; precision is closeness among repeated measurements. A precise set can be biased.
- A hypothesis is a testable prediction; a theory is a well-supported explanatory framework; a law describes a consistent relationship.
- In calculations, multiplication and division keep the least number of significant figures; addition and subtraction keep the least number of decimal places.
Worked example
A student measures a metal sample as 12.45 g and its volume as 3.2 mL. Density is 12.45 g ÷ 3.2 mL = 3.890625 g/mL. Because 3.2 mL has two significant figures, the answer is 3.9 g/mL. If the student instead reported 3.89 g/mL, the value would be more precise than the volume measurement justifies.
Traps that cost marks
Do not call a theory “just a guess,” or a law “proven beyond doubt.” Do not confuse precision with accuracy. Do not keep extra digits through a multi-step calculation and round only at the end improperly; carry guard digits, then round. Avoid claiming causation from an observational correlation without controlling confounders.