This set practises choosing controls, spotting sample-size limits, drawing graphs, separating repeatability from validity and writing specific improvements. The questions run from easy to harder. All data are invented for practice.
Attempt each question before opening the answer. The overview of the topic is Biology data and investigations. The mistake log and retest queue can help you record what you miss.
Questions
1. (Easy) A student tests whether a plant extract slows the growth of mould on bread, using 2 cm³ of extract on one slice. Suggest a control.
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A slice of the same bread in an identical dish, given 2 cm³ of water instead of the extract, kept in the same place for the same time. It shows whether mould growth changes because of the extract and not because the bread was made wet.
2. (Easy) In an experiment on light intensity and photosynthesis in pondweed, name three control variables.
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Any three of: temperature of the water, carbon dioxide supply (for example the same hydrogencarbonate solution), the same pondweed and length, time of counting, type of lamp. Each stays the same at every light intensity.
3. (Easy) Three bean seedlings in a new compost grew 8, 9 and 16 cm. Three in normal compost grew 10, 11 and 12 cm. Calculate both means and say what you can conclude.
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New compost: (8 + 9 + 16) ÷ 3 = 33 ÷ 3 = 11 cm. Normal compost: (10 + 11 + 12) ÷ 3 = 33 ÷ 3 = 11 cm.
The means are equal, so there is no evidence of a difference. The new compost group has a wider spread (range 8 cm against 2 cm), and with only three seedlings per group the result cannot be trusted either way. Use a larger sample, for example 20 per group.
4. (Medium) A student cuts potato cylinders and places them in sucrose solutions. The percentage change in mass after 30 minutes was: 0.0 mol/dm³: +18; 0.2: +8; 0.4: −2; 0.6: −10; 0.8: −16. State what goes on each axis with labels, suggest a scale for the y axis, and estimate the concentration where there is no change in mass.
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x axis: “Concentration of sucrose solution / mol/dm³” (the variable changed). y axis: “Change in mass / %” (the variable measured).
y scale: values run from −16 to +18, a span of 34. Use 5% per large square from −20 to +20, which fills the grid and uses easy steps. Mark zero clearly on the y axis.
Estimate: the line crosses zero between 0.2 (+8) and 0.4 (−2). The change is −10 over 0.2 mol/dm³, so going from +8 down to 0 takes 8 ÷ 10 × 0.2 = 0.16. The estimate is 0.2 + 0.16 = about 0.36 mol/dm³. It is an estimate read from a line between measured points.
5. (Medium) The repeats of a bubble count at one temperature were 12, 14, 13 and 25 bubbles per minute. Identify the anomaly, then calculate the mean with and without it.
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The anomaly is 25, far from the others, which lie between 12 and 14.
With it: (12 + 14 + 13 + 25) ÷ 4 = 64 ÷ 4 = 16. Without it: (12 + 14 + 13) ÷ 3 = 39 ÷ 3 = 13. The mean excluding the anomaly represents the typical result better, and the anomaly should be investigated, for example a miscounted or missed bubble.
6. (Medium) Decide whether each statement describes repeatability or validity. (a) Three readings were 31, 33 and 32. (b) Yeast mass was the same in every tube. (c) Two classmates using the same method got results within 1 unit of each other.
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(a) Repeatability: the repeated readings agree closely.
(b) Validity: a variable was controlled, so the comparison is fair.
(c) Repeatability or reproducibility depending on your course wording: different people gave similar results. State your definition in the answer. Check how your teacher or syllabus uses the terms.
7. (Medium) Rewrite each vague suggestion so it is specific. (a) “Use better equipment to measure the gas.” (b) “Keep the temperature the same.”
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(a) “Collect the gas in a gas syringe with 1 cm³ divisions and record the volume after a set time, instead of counting bubbles of uneven size, so the measurement is more precise.”
(b) “Place each tube in a water bath at 30 °C and check it with a thermometer, so the temperature is the same for every repeat.”
8. (Harder) A student counts bubbles of gas from yeast for 2 minutes and gets 26, 30 and 28 bubbles in three repeats. Calculate the mean rate in bubbles per minute.
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Mean count = (26 + 30 + 28) ÷ 3 = 84 ÷ 3 = 28 bubbles in 2 minutes.
Rate = 28 ÷ 2 = 14 bubbles per minute.
Check: each count divided by 2 gives 13, 15 and 14, and their mean is 42 ÷ 3 = 14. The repeats have a range of 4 bubbles, so they are reasonably repeatable.
9. (Harder) A model predicts that crossing two heterozygous tall pea plants gives a 3:1 ratio of tall to dwarf. A student observes 5 tall and 3 dwarf from 8 offspring. Is this evidence against the model? Explain.
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The model predicts 6 tall and 2 dwarf from 8 offspring, and the observation is 5 and 3, only one offspring different. With such a small sample, chance easily explains this gap, so it is not good evidence against the model. A larger sample, for example 200 offspring, is expected to give numbers closer to 150 tall and 50 dwarf.
10. (Harder) A student tests the effect of salt on radish seed germination. She puts 10 seeds in one dish per salt concentration, using a large dish for the highest concentration and a small dish for the lowest. She counts germinated seeds once after 3 days. Suggest a control, name one limitation and give one specific improvement.
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Control: a dish with 10 seeds and the same volume of distilled water with no salt.
Limitation (validity): the dish size changed along with salt concentration, so the result may be due to spacing or water contact and not to the salt. There is also only one dish per concentration, so repeatability cannot be judged.
Improvement: use identical dishes with the same volume of solution, and repeat each concentration with three dishes of 10 seeds, calculating a mean number germinated.
If you got these wrong
- Questions 1, 2 and 10 (controls): revisit choosing a control.
- Questions 3 and 9 (small samples): revisit identifying a sample-size limitation. The inheritance model board also shows small samples against a model.
- Question 4 (graphs): revisit drawing an interpretable graph.
- Questions 5, 6 and 8 (repeats, means, rates): revisit repeatability and validity.
- Questions 7 and 10 (improvements): revisit making improvements specific.
A pattern across your wrong answers usually points to a single habit, such as leaving out a number or a reason. Online one-to-one Biology tuition can work on that habit with your own written answers.