- Specification route
- PS
- Question bank
- 12 questions
- Course stage
- AS / Year 12
Sample questions
What is the difference between 'accuracy' and 'precision' in experimental measurements?
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You can reliably hit the exact same wrong spot on a dartboard. That is precise, but not accurate.
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Answer: Accuracy is how close a measurement is to the true value, whereas precision is how close repeated measurements are to each other.
Practical Skills (PS 3.3). Accuracy is proximity to the true value. Precision relates to the spread of repeated measurements; tight clustering means high precision, even if they are all inaccurate due to a systematic error.
In an experiment measuring the effect of temperature on the rate of an enzyme-controlled reaction, the student uses a buffer solution. What type of variable is the pH in this experiment?
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The student is actively keeping it constant so it doesn't affect the results.
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Answer: A control variable
PS 2.4. A control variable is one that is kept constant to ensure a valid test. Since temperature is the independent variable, pH must be controlled (using a buffer) so it does not affect the dependent variable (reaction rate).
A student is plotting the results of an experiment investigating the effect of varying light intensity (lux) on the rate of photosynthesis (bubbles/min). Which type of graph is most appropriate?
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Lux can be any numerical value, and the rate can be any numerical value.
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Answer: A scatter graph with a line or curve of best fit, because both variables are continuous.
PS 3.1. When both the independent variable (light intensity) and dependent variable (rate) are continuous, a scatter graph (often with a line of best fit) is the correct way to display the relationship.
In an experiment testing the effect of an antimicrobial substance, a paper disc soaked *only* in sterile water is placed on the agar plate. What is the purpose of this?
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You must prove that the active ingredient is the *only* thing doing the killing.
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Answer: It acts as a negative control to prove that any zone of inhibition is caused by the antimicrobial substance itself, not the paper disc or the water.
PS 2.1 / CPAC 2. A control experiment isolates the independent variable. The water disc proves that the physical presence of the disc and the solvent do not inhibit bacterial growth.
When looking at a data table, how would a student identify an 'anomalous' result?
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An anomaly is an outlier; the 'odd one out'.
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Answer: It is a measurement that deviates significantly from the general trend of the data or is vastly different from the other repeats at that specific independent variable value.
PS 3.2. Anomalous results are data points that do not fit the overall pattern or vary significantly from repeats. They should ideally be investigated or omitted from mean calculations.
A student plots a bar chart showing the mean resting heart rate of different mammal species. They add error bars to show $\pm 1$ standard deviation. If the error bars for humans and chimpanzees overlap significantly, what can be concluded?
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Overlapping spreads mean the 'true' mean for both groups could easily be the exact same number.
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Answer: There is likely no statistically significant difference between the mean resting heart rates of humans and chimpanzees.
PS 3.3. Standard deviation error bars show the spread of data. If they overlap, it implies that the difference between the two means could just be due to chance, meaning the difference is not significant.
In an experiment, what defines the 'dependent variable'?
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Its value 'depends' on what you do to the experiment.
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Answer: It is the variable that is measured or observed by the researcher to see how it responds to changes in the independent variable.
PS 1.1. The dependent variable is the outcome being measured (e.g., volume of oxygen produced). The independent variable is what you change (e.g., temperature). Control variables are kept constant.
What makes an experimental investigation 'valid'?
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If you are testing how temperature affects plant growth, but you also change the light levels, your test is completely broken.
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Answer: The experiment truly tests what it sets out to test, ensuring that all control variables are kept constant so only the independent variable affects the dependent variable.
PS 2.4. Validity refers to whether the experiment actually measures what it intends to. This requires strict control of confounding variables so that any change in the dependent variable is solely due to the independent variable.
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