Bias in Sampling

Key idea

Systematic errors that make samples unrepresentative.

In depth

Bias is a systematic error that pushes results in one direction. Selection bias, non-response bias and voluntary response bias are common. A bigger sample does not fix a biased design.

Worked example

An online poll about internet use only reaches people who are online, overstating usage.

Real-world uses

• Spotting why an online poll may not reflect the whole population
• Checking a news article’s claims

Common mistake

Believing large samples automatically remove bias.

How to learn this

1. Read the key idea and say it in your own words.
2. Work through the worked example, then try a similar problem.
3. Use the interactive lesson’s visual and mini-quiz to check the pattern.

Frequently asked questions

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Related intermediate topics in Probability & Statistics

• Collecting Data and Sampling – Surveys, experiments and random sampling.
• Histograms – Bars showing frequency of numerical intervals.
• Dot Plots and Stem-and-Leaf Plots – Show the shape of small datasets.
• Mean – The arithmetic average.
• Median – The middle value of an ordered list.
• Range – Difference between maximum and minimum.