Practice Sampling Bias in Statistics

Use these practice problems to test your method after reviewing the concept explanation and worked examples.

Quick Recap

Sampling bias occurs when a sample is collected in a way that systematically makes some members of the population more likely to be included than others, producing results that do not accurately represent the full population and leading to misleading conclusions.

Asking only your friends about favorite music doesn't tell you what the whole school thinks - your friends probably have similar tastes! That's bias. A good sample is like a well-shuffled deck: everyone has an equal chance of being picked.

Example 1

easy
A school wants to know whether students prefer longer lunch breaks. They survey students in the cafeteria at lunchtime. Identify the sampling bias.

Example 2

medium
A website runs an online poll asking 'Should the government raise taxes?' and 90% of respondents say 'No'. Can this result be trusted? Explain what type of bias is present.

Example 3

medium
A researcher wants to estimate the average income of adults in a city. She interviews people at a shopping centre on a weekday morning. Identify two sources of bias in her sampling method.

Example 4

hard
In the 1936 US presidential election, the Literary Digest magazine polled 2.4 million people and predicted Alf Landon would win. Instead, Franklin Roosevelt won in a landslide. The magazine had sampled from telephone directories and car registration lists. Explain why the poll failed despite its enormous sample size.
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