Identifying biased samples Revision Card

AI generatedStatisticsKS3 / GCSE

Identifying biased samples.

Look for groups that are favoured or excluded by the selection method.
Explain how that could affect the answers, then suggest a practical improvement.
A larger sample does not automatically remove bias.

Example 1

A school asks only football club members whether it should spend more on sport. Explain the likely bias and suggest an improvement.

Football club members may favour sports spending. Randomly select students from the whole school.

The selection method favours a group with a particular interest.

A council surveys town residents online about internet access. Explain a likely bias and an improvement.

Residents without internet access are excluded. Offer other response methods and sample across the town.

The way people can respond affects who can be included.

Question 1

A shop asks only customers visiting at 10 am on a weekday about opening hours. Explain a limitation and an improvement.

Check answer

Working customers may be missed. Survey across different times and days.

One time slot may attract a different group from the full customer population.

Question 2

A teacher asks the first ten students to volunteer about homework difficulty. Explain the possible bias.

Check answer

Volunteers may have particularly strong views. Randomly select from the whole class instead.

Willingness to volunteer may be related to the answer.

Question 3

A survey of all school years uses only Year 11 students. Suggest an improvement.

Check answer

Include students from every year, in suitable proportions, with random selection within the groups.

Year 11 experiences may differ from those of younger pupils.

Question 4

A restaurant asks only people leaving five-star reviews about meal quality. Explain the bias.

Check answer

It selects people already known to be very satisfied. Select customers independently of their review rating.

The selection is directly linked to the outcome being measured.

Question 5

A website claims that 20 000 voluntary votes remove all sampling bias. Is that justified?

Check answer

No. A large voluntary sample can still be biased.

Increasing the number of responses does not fix a selection method that systematically misses or favours groups.