Why it matters
Who is missing from the data can matter as much as who is included. A precise summary of a selected sample may still misrepresent the population of interest.
A worked example
Surveying only successful shop owners excludes businesses that closed. Their reported profits may not describe everyone who started a shop.
Illustrative example · simplified assumptionsA common mistake
Assuming sample size alone guarantees representativeness.
Where the idea needs care
Larger samples do not automatically repair a biased selection process. The target population must be defined.
Apply the idea
Explain this concept using a different example from your spending, work, business or a policy debate. State what stays fixed and what could change the result.
See the supporting infographic
The written explanation above is the main lesson. This image offers another way to remember it.
Sources and further study
Examples and explanations by Alibomics. Numeric illustrations are not current market quotations.