OCR A Level Physics B (Advancing Physics)
OCR A Level Physics B Module 2: Fundamental Data Analysis Exam Questions
Free OCR A Level Physics B exam questions for Module 2: Fundamental Data Analysis, with a mark scheme for every pack. Covers uncertainty and resolution, spread of readings, systematic error and outliers, combining uncertainties, and plotting and analysing graphs.
Module 2: Fundamental Data Analysis exam questions
1 question pack of real past exam questions, each with its mark scheme. Do not stop after a few: answer as many as you can without notes, then mark every answer with the mark scheme. The more questions you do, the more quickly you will spot how examiners ask about each idea.
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About OCR A Level Physics B Module 2: Fundamental Data Analysis
Module 2 of OCR A Level Physics B (Advancing Physics), Fundamental Data Analysis, teaches the measurement and data skills used in every other module. It covers the resolution of instruments, estimating uncertainty from the spread of repeated readings, spotting systematic errors and outliers, combining uncertainties, and plotting graphs with error bars to find gradients and intercepts with their uncertainties. Advancing Physics places a strong emphasis on evaluating real data, so these skills are tested throughout the papers, especially in practical-focused questions. Examiners look for sensible significant figures, correctly stated uncertainties, clear identification of the largest source of uncertainty, and justified conclusions from graphs.
What you need to know
- Resolution and uncertainty Resolution is the smallest change an instrument can detect. The uncertainty in a set of repeated readings can be estimated as plus or minus half the range (the spread), and the result quoted as mean plus or minus uncertainty.
- Systematic error and outliers Systematic errors shift all readings in the same direction, such as a zero error or a poorly calibrated meter. Outliers should be checked and repeated rather than simply ignored.
- Percentage uncertainty Percentage uncertainty = (uncertainty / value) x 100. Identify the quantity with the largest percentage uncertainty, as improving it has the biggest effect.
- Combining uncertainties When values are added or subtracted, add absolute uncertainties; when multiplied or divided, add percentage uncertainties; for a power, multiply the percentage uncertainty by the power.
- Graphs Plot data with error bars, draw a line of best fit and the steepest and shallowest acceptable lines, and use them to find the gradient, intercept and their uncertainties. Linearise relationships, for example by plotting log graphs.
Common mistakes in Module 2: Fundamental Data Analysis
- Quoting a mean to more significant figures than the data justify. Round the result so it matches the size of its uncertainty.
- Confusing resolution with uncertainty. Resolution is a property of the instrument; uncertainty also depends on the variation in repeated readings.
- Removing an anomalous result without explanation. Check for a reason, repeat the measurement if possible, and state why it was excluded.
- Thinking repeat readings reduce systematic error. Repeats reduce the effect of random variation but cannot remove a systematic error such as a zero error.
- Drawing worst fit lines that miss the error bars. The steepest and shallowest lines must still pass through all the error bars.
Try three Module 2: Fundamental Data Analysis exam-style questions
1. Repeated readings of a time are 2.31 s, 2.35 s, 2.28 s and 2.34 s. State the mean and its uncertainty, and calculate the percentage uncertainty. (3 marks)
Show the mark scheme answer
Mean = 9.28 / 4 = 2.32 s; uncertainty = half range = (2.35 - 2.28) / 2 = 0.035, so about plus or minus 0.04 s; percentage uncertainty = 0.035 / 2.32 x 100 = 1.5%.
2. The length and width of a sheet are measured with percentage uncertainties of 0.5% and 2.0%. Calculate the percentage uncertainty in its area and state which measurement to improve. (2 marks)
Show the mark scheme answer
Area uncertainty = 0.5 + 2.0 = 2.5%; improve the width measurement as it contributes the larger uncertainty.
3. Explain how a systematic error could be identified from a graph that should pass through the origin. (2 marks)
Show the mark scheme answer
The best fit line is straight but has a non-zero intercept; showing every reading is shifted by the same amount, such as a zero error.
Module 2: Fundamental Data Analysis FAQs
What does OCR A Level Physics B Module 2: Fundamental Data Analysis cover?
Measurement, resolution, uncertainty, spread of data, systematic error, outliers, combining uncertainties and analysing graphs.
Where are Fundamental Data Analysis skills tested?
They are applied across the whole course and appear frequently in questions on practical work and data evaluation.
How should I practise data analysis?
Take real data from your practicals, calculate means and half-range uncertainties, plot graphs with error bars, and find gradient uncertainties using worst fit lines.
