AQA · GCSE · Biology
Course version: 8461 · Version from Sept 2018
Students should understand the principles of sampling as applied to…
Full specification wording
Health issues: Students should understand the principles of sampling as applied to scientific data, including epidemiological data.
Sampling means studying a subset of a population to draw conclusions about the whole population.
Checked against the AQA 8461 specification (opens in a new tab) on .
- Point 10 of 10
- 3 key terms
Study notes
From the checked teaching notes for this specification point.
The idea
Sampling means studying a subset of a population to draw conclusions about the whole population. Because it is usually impossible to measure every person, researchers select a sample. A representative sample reflects the population's key features, such as age, sex and location, so results can be generalised. Random sampling gives every member an equal chance of selection and reduces bias. Sample size matters: larger samples usually give more reliable estimates, though they take more time and resources. In epidemiology, scientists sample populations to estimate disease incidence, identify risk factors and monitor outbreaks.
For example: Testing a random sample of 1,000 people for a disease can estimate its prevalence in a city, but the estimate is uncertain and may not represent groups left out of the sample.
What earns the marks
- Define sampling as studying a subset of a population to make inferences about the whole.
- Explain that a representative sample reflects the characteristics of the population.
- Describe random sampling as giving every member of the population an equal chance of selection.
- Explain that larger samples generally give more reliable estimates than smaller samples.
- Apply sampling principles to epidemiological data, such as estimating disease incidence or prevalence.
- Recognise that biased or unrepresentative samples can lead to invalid conclusions.
Common mistakes and how to put them right
Assuming a sample always represents the population.
Put it right by checking whether the sample is representative and large enough.
Confusing random sampling with haphazard or convenience sampling.
Put it right by explaining that random sampling gives every member an equal chance of selection.
Thinking a larger sample guarantees a perfect result.
Put it right by stating that larger samples usually improve reliability but do not remove all error or bias.
Exam tips
- Use the phrase 'representative of the population' when explaining why a sample is useful.
- Link sample size to reliability: larger samples generally give more reliable estimates.
- When evaluating epidemiological data, comment on who was sampled, how they were selected and whether the sample was large enough.
Try the lesson
The start of the Health issues: Students should understand the principles of sampling as applied to scientific data, including epidemiological data. lesson, made from checked teaching notes for this specification point.
Have a go first
Why do scientists take a sample when studying disease incidence in a large population?
Listen
Sampling means studying a subset of a population to draw conclusions about the whole population. Because it is usually impossible to measure every person, researchers select a sample. A representative sample reflects the population's key features, such as age, sex and location, so results can be generalised. Random sampling gives every member an equal chance of selection and reduces bias. Sample size matters: larger samples usually give more reliable estimates, though they take more time and resources. In epidemiology, scientists sample populations to estimate disease incidence, identify risk factors and monitor outbreaks. For example, testing a random sample of 1,000 people for a disease can estimate its prevalence in a city, but the estimate is uncertain and may not represent groups left out of the sample. A strong answer earns marks for these points. Define sampling as studying a subset of a population to make inferences about the whole. Explain that a representative sample reflects the characteristics of the population. Describe random sampling as giving every member of the population an equal chance of selection. Explain that larger samples generally give more reliable estimates than smaller samples. A common slip: Assuming a sample always represents the population. Instead, checking whether the sample is representative and large enough. Exam tip: Use the phrase 'representative of the population' when explaining why a sample is useful.
Key words
Say what each word means before you turn the card.
Sampling
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Representative sample
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Random sampling
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See every definition
- Sampling
- Studying a subset of a population to draw conclusions about the whole population.
- Representative sample
- A sample that reflects the population's key features, such as age, sex and location, so results can be generalised.
- Random sampling
- Selection that gives every member of the population an equal chance of selection and reduces bias.
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