In the case of ACS data, the issue with statistics like these is not just privacy but also sample size. The margins of error are generally high for block group counts, and even more so for smaller subpopulations, so poverty rate by race/ethnicity would…

What do you mean by maximize data analysis? Do you mean reduce the margins of error? If so, pooling across multiple weeks is one way to increase sample size and improve reliability of estimates...

https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018_ch08.pdf

For how to compute the MoE (Margin of Error) for a %.   Note these formulas are approximate and need some adjustment near 0 or 100 %

Dave Dorer

Hi Spence, looks like you're getting nulls for the fields that end in EA (estimate annotation) and MA (margin of error annotation) which are essentially the footnotes when there are asterisks or other symbols in the table instead of numbers. This table…

Dear Steve,

Don't forget that the ACS is a survey and the numbers in the tables are survey/sample estimates. A census is a count of "everybody" and there is no "margin of error"

As a general matter you can look at tract level estimates…

Aggregating the data to larger geographic areas is one potential solution if you are encountering large margins of error or zero values. Seth Spielman also described some potential strategies/pitfalls related to data aggregation in a 2015 paper:

https…

Hi Liliam -

In a typical year there is not much change from one 5-year ACS estimate to the next because 4 of the 5 years are the same (data for 2016, 2017, 2018, and 2019 show up in both the 2019 5-year and 2020 5-year). In addition the number of households…