Sampling Bias Statistics Example 3
Follow the full solution, then compare it with the other examples linked below.
Example 3
mediumA 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.
Solution
- 1 Step 1: Bias 1 — Location bias: people at a shopping centre may have more disposable income than the general population, skewing the average upward.
- 2 Step 2: Bias 2 — Time bias: weekday morning shoppers exclude people who work traditional hours (typically higher earners in some sectors and lower earners who cannot take time off), creating a non-representative sample.
Answer
Two biases: (1) location bias — shopping centre visitors may not represent all income levels, and (2) time bias — weekday morning excludes people working traditional hours.
Sampling bias can arise from multiple sources simultaneously. Both the location and timing of data collection can systematically exclude segments of the population, making the sample unrepresentative. Random sampling from a complete list of the population would avoid these biases.
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 mediumA website runs an online poll asking 'Should the government raise taxes?' and 90% of respondents say
Example 4 hardIn the 1936 US presidential election, the Literary Digest magazine polled 2.4 million people and pre