Scientific Inquiry, Measurement, and Data Analysis
Scientific Inquiry, Measurement, and Data Analysis
This domain tests experimental design, metric measurement, graphing, and the interpretation of data with appropriate units and uncertainty.
Core rules and concepts
- A testable hypothesis predicts a relationship. The independent variable is changed, the dependent variable is measured, and constants are held fixed; a control group provides a baseline.
- Use metric units: meter, kilogram, second, kelvin; density in g/cm³. Convert carefully before calculating.
- Percent error = |measured − accepted| ÷ accepted × 100%.
- Graphs: independent variable on the x-axis, dependent variable on the y-axis. Line graphs show continuous change; slope is a rate. Interpolation estimates within data; extrapolation estimates beyond data and is less reliable.
- Accuracy is closeness to the accepted value; precision is repeatability. Report units and reasonable significant figures.
Worked example
A student measures a rock’s density as 4.8 g/cm³; the accepted value is 5.5 g/cm³. Percent error = |4.8 − 5.5| ÷ 5.5 × 100% = 0.7 ÷ 5.5 × 100% ≈ 12.7%, or about 13%. If repeated trials cluster near 4.8, the result is precise but not accurate.
Traps that cost marks
- Switching the x- and y-axes on a graph.
- Using a bar graph for continuous data.
- Ignoring units or failing to convert centimeters to meters.
- Treating a precise set of measurements as automatically accurate.