OCR A Level Biology: Development of Practical Skills — Practice Questions

These are original questions written for Marlbridge, for revision and practice on this content. They are not reproduced past-paper questions, and they do not replicate the exam’s exact structure, question count or mark tariffs — examination boards hold copyright in their own papers. Use these alongside the official past papers available free from your board.

Related: Development of Practical Skills revision notes

In OCR’s H420 papers, Biological processes (H420/01) and Biological diversity (H420/02), each 100 marks, open with a Section A of multiple-choice questions worth 15 marks, followed by a Section B of short-answer and extended-response questions worth 85 marks; Unified biology (H420/03, 70 marks) has no multiple-choice section. The multiple-choice sample below is scoped to this topic (Development of Practical Skills) only, and is not a reproduction of a full paper’s Section A.

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Section A — Multiple choice (topic sample)

1. A student’s experiment produces precise, repeatable results, but the student fails to control a confounding variable. The results are: A) Reliable and valid B) Reliable but not valid C) Valid but not reliable D) Neither reliable nor valid [1]

2. A thermometer reads to a resolution of ±0.5°C and is used to record a temperature of 25°C. What is the percentage uncertainty in this single reading? A) 0.5% B) 1% C) 2% D) 5% [1]

3. Which statistical test should be used to test for an association between two variables measured on an ordinal (ranked) scale? A) Student’s t-test B) Chi-squared test C) Spearman’s rank correlation D) Standard deviation [1]

4. A student always begins timing 2 seconds after mixing the reagents, because of a consistent reaction time. This is an example of: A) Random error, which is corrected by repeating and averaging B) Systematic error, which repeating the measurement will not remove C) An anomaly, which should be excluded from the mean D) An improvement in accuracy [1]

5. A set of repeat readings has a small standard deviation relative to the mean. This indicates that: A) The data is not valid B) The repeated measurements are closely clustered around the mean, indicating good precision C) There is a systematic error present D) The sample size is too small to be meaningful [1]

6. Why should an anomalous result be identified and excluded before calculating a mean, rather than included alongside the other readings? A) Including it would improve the precision of the mean B) Including it is likely to bias the mean away from the true value C) It converts a systematic error into a random one D) It has no effect on the mean either way [1]

7. Which statistical test is appropriate for comparing observed and expected frequencies of categoric data? A) Student’s t-test B) Chi-squared test C) Spearman’s rank correlation D) Pearson’s product-moment correlation coefficient [1]

8. Pearson’s product-moment correlation coefficient is the appropriate test for which situation? A) Testing an association between two ranked, ordinal variables B) Testing an association between two continuous, normally distributed variables C) Comparing observed and expected frequencies D) Comparing the means of two independent groups [1]

9. In a statistical significance test, what does the null hypothesis state? A) There is a significant difference or association between the variables tested B) There is no significant difference or association between the variables tested C) The experiment has been designed correctly D) The sample size is large enough to draw a conclusion [1]

10. Why are individuals or samples often selected using random sampling in a biological investigation? A) It guarantees the sample will be identical to the whole population B) It reduces the risk of a biased, unrepresentative sample C) It removes the need for repeat readings D) It eliminates random error entirely [1]

11. A student uses a burette reading to ±0.05 cm³ and takes an initial and a final reading to obtain a titre of 20.0 cm³. What is the percentage uncertainty in this titre? A) 0.25% B) 0.5% C) 1.0% D) 0.05% [1]

12. A student replaces a measuring cylinder with a pipette of finer resolution to measure the same volume of solution. What is the effect on percentage uncertainty? A) It increases, because a pipette has a smaller absolute uncertainty B) It decreases, because a smaller absolute uncertainty is now a smaller proportion of the measured volume C) It stays the same, since percentage uncertainty depends only on the volume measured D) It cannot be determined without repeating the measurement [1]

13. A student extrapolates a graph beyond the range of the data actually collected. What is the main risk of doing this? A) The extrapolated region will always show a slower rate than the true value B) The trend may not continue in the same way beyond the collected data, making conclusions there less reliable C) Extrapolation always converts a valid method into an invalid one D) It removes the need to calculate a mean for the collected data [1]

14. To find the rate of reaction at one specific point on a curved graph of product formed against time, a student should: A) Divide the final product amount by the total time B) Measure the gradient of the tangent to the curve at that point C) Measure the gradient of a straight line joining the first and last points D) Read the y-value at that point directly as the rate [1]

15. What is meant by the “range” of a set of repeat data? A) The mean of the highest and lowest values B) The difference between the highest and lowest values C) The number of repeat readings taken D) The standard deviation of the data set [1]

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Section B — Short answer and extended questions

16. Define independent variable, dependent variable and control variable. [3]

17. Explain the difference between accuracy, precision and reliability. [3]

18. A student investigates the effect of sucrose concentration on the mass change of potato discs.

(a) State the independent and dependent variables. [2] (b) Give three variables that must be controlled and explain why each matters. [6] (c) Explain why percentage change in mass is used rather than absolute change. [2] (d) Describe how the student should improve the reliability of the results. [2]

19. A balance reads to ±0.01 g and a disc has a mass of 2.50 g.

(a) Calculate the percentage uncertainty in a single reading. [2] (b) Explain how percentage uncertainty could be reduced. [2]

20. Explain the difference between a systematic and a random error, giving an example of each and how to deal with it. [4]

21. State whether a line graph, bar chart or scatter graph is appropriate for each, with a reason:

(a) mean height of plants grown in four different soil types [2] (b) rate of reaction against temperature [2]

22. Distinguish between a control variable and a control experiment. [3]

23. An enzyme investigation records these times to a fixed end point at 30°C: 38 s, 40 s, 39 s, 65 s, 41 s. Identify the anomaly, calculate the mean of the remaining readings, and state the rate. [4]

24. A student wants to test whether there is a significant difference between the mean leaf lengths of two plant species. Which statistical test should be used, and what does it mean if the calculated value exceeds the critical value at p = 0.05? [3]

25. State which statistical test is appropriate for testing an association between two continuous variables. [1]

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Answers

1. B) Repeatable, closely-clustered results are reliable, but without controlling the confounding variable the experiment does not measure what it claims to, so the results are not valid [1].

2. C) Percentage uncertainty = (0.5 ÷ 25) × 100 = 2% [1].

3. C) Spearman’s rank correlation tests for an association between two ranked (ordinal) variables; the t-test compares two means, the chi-squared test compares observed and expected frequencies of categoric data, and standard deviation is a measure of spread rather than a test of association [1].

4. B) A consistent delay affects every reading in the same way and by the same amount, so it is a systematic error; repeating the measurement and averaging will not remove it, unlike a random error, which repeats and averaging can reduce [1].

5. B) A small standard deviation relative to the mean shows the repeated measurements are closely grouped together, which indicates good precision; it says nothing on its own about validity, systematic error, or sample size [1].

6. B) An anomalous result lies well outside the pattern of the other repeats, most likely because of a one-off procedural error, and including it would pull the calculated mean away from the value the other, consistent readings point to [1].

7. B) The chi-squared test compares observed frequencies against expected frequencies for categoric data; the t-test compares two means, Spearman’s rank tests ordinal association, and Pearson’s tests continuous association [1].

8. B) Pearson’s product-moment correlation coefficient tests for a linear association between two continuous variables that are (approximately) normally distributed; Spearman’s rank is used instead when data is ordinal or not normally distributed [1].

9. B) The null hypothesis states there is no significant difference or association between the variables being tested; a significance test either rejects this in favour of the alternative hypothesis or fails to reject it — it does not itself assert a real difference exists [1].

10. B) Random sampling gives every individual in the population an equal chance of selection, which reduces the risk that the sample happens to over-represent one kind of individual and so misrepresents the wider population [1].

11. B) A titre requires two burette readings (initial and final), each with an uncertainty of ±0.05 cm³, so the combined absolute uncertainty is 2 × 0.05 = 0.10 cm³ [1]; percentage uncertainty = (0.10 ÷ 20.0) × 100 = 0.5% [1].

12. B) Percentage uncertainty = absolute uncertainty ÷ measured value × 100, so a finer-resolution pipette with a smaller absolute uncertainty gives a smaller percentage uncertainty for the same measured volume, even though the volume itself is unchanged [1].

13. B) Beyond the range of the data actually collected, there is no direct evidence that the same trend continues, so a conclusion drawn from the extrapolated portion of the line is less reliable than one drawn from within the measured range [1].

14. B) On a curved graph, the rate at one specific point is found from the gradient of the tangent drawn to the curve at that point, not from an average taken across the whole curve or a single y-value alone [1].

15. B) The range is the difference between the highest and lowest values in a data set, giving a simple measure of how spread out the repeats are [1].

16. Independent — the variable deliberately changed by the investigator [1]. Dependent — the variable measured as a result [1]. Control — a variable kept constant so it does not affect the dependent variable [1].

17. Accuracy — how close a measurement is to the true value [1]. Precision — how closely repeated measurements agree with one another, regardless of whether they are correct [1]. Reliability — the extent to which repeats give consistent results, so the conclusion can be trusted [1].

18. (a) Independent: sucrose concentration [1]. Dependent: change in mass of the potato discs [1]. (b) Any three, each for 2 marks: temperature — affects the rate of osmosis and therefore the mass change in a fixed time [1] [1]. Time in solution — discs left longer would approach equilibrium more closely [1] [1]. Surface area / size of disc — a larger area allows faster water movement [1] [1]. Same potato / same tissue — different potatoes have different internal solute concentrations [1] [1]. (c) The discs will not all start with exactly the same mass [1], so percentage change allows a fair comparison between discs of different starting masses [1]. (d) Repeat each concentration at least three times and calculate a mean [1], and identify and discard anomalous results rather than including them in the mean [1].

19. (a) (0.01 ÷ 2.50) × 100 [1] = 0.4% [1]. (b) Use a larger mass, for example by weighing several discs together [1], since the absolute uncertainty stays the same while the measured value increases [1]. (Or use a balance with a finer resolution.)

20. Systematic — an error that shifts every reading by the same amount in the same direction, e.g. a balance that is not zeroed [1]; dealt with by calibrating or zeroing the instrument, since repeats will not remove it [1]. Random — an error that varies unpredictably in size and direction, e.g. judging when a colour change is complete [1]; reduced by taking repeat readings and calculating a mean [1].

21. (a) Bar chart [1], because soil type is a categoric (discrete) variable [1]. (b) Line graph [1], because both variables are continuous and there is an expected relationship between them [1].

22. A control variable is a factor kept constant during the experiment so it does not itself affect the dependent variable [1]. A control experiment is a separate, parallel run in which the factor under test is absent — for example, boiled enzyme in place of active enzyme [1] — used to confirm the observed effect is genuinely caused by that factor and not some other confound [1].

23. 65 s is anomalous and should be discarded [1]. Mean of the remaining readings = (38 + 40 + 39 + 41) ÷ 4 = 39.5 s [1] [1]. Rate = 1 ÷ 39.5 = 0.0253 s⁻¹ [1].

24. A t-test [1], since it compares the difference between two means [1]. If the calculated value exceeds the critical value, the difference is significant and the null hypothesis is rejected — meaning there is less than a 5% probability the difference arose by chance [1].

25. A correlation coefficient [1].

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Where marks are usually lost

• Confusing accuracy with precision.
• Naming control variables without saying why they matter.
• Forgetting that repeats improve reliability and the accuracy of the mean by reducing random error, but do nothing for a systematic error, which needs calibration.
• Using a bar chart for two continuous variables.
• Confusing a control variable with a control experiment.
• Calculating a mean before identifying and discarding anomalous readings.
• Choosing a correlation coefficient when comparing two means, or a t-test when testing an association.