Here are some potential limitations of generalizing census findings back to the entire population:
- Undercounting - Certain groups like minorities, homeless, and immigrants tend to be undercounted in the census. This can skew results when generalizing back to the whole population.
- Nonresponse bias - People who do not respond to the census are likely different from those who do respond in key ways. This self-selection limits generalizability.
- Sampling errors - Even though the census attempts to count the entire population, some sampling is still used which introduces small amounts of error.
- Changes over time - The population changes between census counts, so projecting older census data onto the current population may be inaccurate.
- Optional questions - Some census questions are optional, so missing data on key variables may limit generalizations.
- Context shifts - Social, political, economic contexts change over time, affecting how census responses reflect the overall population.
- Categorization - How questions and populations are categorized can affect results (e.g. race/ethnicity classifications may be limiting).
So in summary, undercounting, nonresponse biases, sampling errors, temporal changes, missing data, shifting contexts, and categorical limitations can all affect the census's representativeness and generalizability. Large sample sizes alone do not guarantee lack of bias or error in a descriptive study.