Ever since the US Census Bureau changed from the old, reliable decennial census (every ten years we all gave our stats to the Federal Government), we've had the joy of 'relying' on the shiny new, ever-changing American Community Survey. This is a census that takes rather small samples of US people every year. That sounds good right, except there are bugs. We'll call them errors to be honest. This website is an attemptedly humorous attempt to help people understand what this may mean for a city like Oakland.
With the ACS comes a thing called a Margin of Error (MOE), this means that for every amazingly reassuring statistic you see from this data source (most things you've read this past three years), there is a hidden truth- the number you see isn't so much the truth, as much as a number somewhere in the middle of a range of possible truths. To really understand this well takes a statistics degree. Luckily we have some of those, but this still is a mess and we hope this randomization map helps you understand this. If you look at the map, you'll see one of very many possible truths for Oakland. Hit the Randomization button and you'll see another, equally likely reality. Not possible? Wrong, sorry. When the data comes from a small sample each year, there are rather large errors in data such as the indicator for Households in Poverty. A certain census tract may get labelled with the real/truthy value of 40% poverty, but because the errors are very large in Oakland's tracts, the true number may very well be anywhere from an impressively low number of 20% or as tragically high as say 55%.Yes this is a bad situation. Yes it means you, (and we) need to take American Community Survey data with a large bag of salt. If you don't not see any error margins (a range where any number inside that range is just as likely as any other in said range), then you SHOULD ask the authors for that data. Given how drastically our map of Oakland can change and still be a "truthful" representation of the ACS data, this is not just a geeky issue- planners, policy makers and grant makers need to care about this.