Sampling Bias Statistics Example 4

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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.

Solution

  1. 1
    Step 1: In 1936, during the Great Depression, telephones and cars were luxuries owned primarily by wealthier individuals. The sampling frame (phone/car owners) systematically excluded lower-income voters who strongly supported Roosevelt.
  2. 2
    Step 2: Large sample size does not fix sampling bias. A biased sample of 2.4 million is less reliable than a well-designed random sample of 2,000. The sample was large but not representative.

Answer

The poll failed because its sampling frame (telephone and car owners) excluded lower-income voters who favoured Roosevelt. No amount of sample size can compensate for systematic sampling bias.
The 1936 Literary Digest poll is a classic example showing that sample size cannot overcome sampling bias. A large biased sample magnifies the bias rather than reducing it. Representative sampling requires that every member of the population has a known chance of being selected.

About Sampling Bias

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.

Learn more about Sampling Bias →

More Sampling Bias Examples

Example 1 easy

A school wants to know whether students prefer longer lunch breaks. They survey students in the cafe

Example 2 medium

A website runs an online poll asking 'Should the government raise taxes?' and 90% of respondents say

Example 3 medium

A researcher wants to estimate the average income of adults in a city. She interviews people at a sh

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