IB Physics HL S2.2.3 Data Quality Questions

Assess HL data quality by identifying systematic error, estimating gradient uncertainty and explaining why repeated measurements improve precision.

Exam points

Identify systematic and random errors from data patterns, error bars and departures from expected relationships.
Improve reliability and precision by repeating measurements, averaging appropriately and reducing percentage uncertainty.
Use uncertainty information, trend-line fit and independent checks to judge data quality and the strength of experimental conclusions.

[Maximum number: 1]

A student attaches one end of a copper wire to an oscillator operating at a fixed frequency. The other end of the wire passes over a pulley to weights that hang vertically. The first harmonic standing wave is established by using the slider to change the length of the wire. The procedure is repeated for different weights.

Figure for Question IB Physics HL S2.2.3 Data Quality Questions question 1 — IB Physics HL

The mass m of the weights and the wavelength $\lambda$ of the wave are related by

m=\frac{\mu f^{2}}{g} \lambda^{2}

where $\mu$ is a constant, f is the frequency of the wave and $g=9.8 \mathrm{~ms}^{-2}$ .

The graph shows the data obtained by the student, plotted to show the variation of m with $\lambda^{2}$ .

Identify the evidence for a systematic error in the data.

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IB Physics HL S2.2.3 Data Quality Questions question 1