Science Inquiry Skills: Designing, Measuring and Judging Data
What you must understand
Science Inquiry Skills is about how physics knowledge is produced and tested. You need to distinguish independent, dependent and controlled variables, write a testable hypothesis (a predicted relationship, not a guess), and choose a design that isolates one variable at a time. Understand reliability (repeatability: repeat trials, average them, control conditions) versus validity (does the method actually measure the intended quantity?). Know how to construct and read tables and graphs, including line of best fit, gradients, intercepts and uncertainty.
Traps
- Confusing accuracy with precision: a precise set of readings can be inaccurate if there is a systematic error (e.g. zero error on a balance or a stopwatch started late).
- Quoting too many significant figures, or averaging readings without considering instrument resolution.
- Describing a trend as linear when the data curve; forcing a straight line through the origin when the physics does not require it.
- Suggesting an improvement that changes the variable being tested.
Rule of thumb and worked example
Uncertainty of a single reading is usually half the smallest scale division; for repeated readings, quote the spread. If a ruler has 1 mm divisions, a single length is quoted as (e.g.) 24.0 ± 0.5 mm.
Worked example: a student times 10 swings of a pendulum to reduce reaction-time error. Total time = 18.4 s, so period = 1.84 s. The stopwatch resolution is 0.01 s, so the timing uncertainty is about ±0.05 s (human reaction dominates), giving period uncertainty ±0.005 s. Timing many swings reduces percentage error; it does not remove a systematic error such as a mis-set zero.