This is mostly an example of a kind of survey bias I’m having trouble finding the name for plus a counterintuitive effect of averaging.

For the bias, when people are asked to estimate a percentage, they tend to estimate by large fractions of the whole, like by quarters, fifths, or tenths. This means you’ll see survey estimates closer to 50% than the real value, with the effect more pronounced for real values closer to 100% or 0%.

For the averaging phenomenon, when looking at the averaged responses across all questions of a survey, you can quite easily get a collection that wouldn’t make sense as a set of responses for “the average” (that is, the typical) person. You can have 3 different responders who each think California, Texas, or Florida has more people than they actually do, and then when you average those responses it looks like all responders think all three of those states have more people than they do, even when no one response was biased that way.

With these two together, this survey makes the average (statistical mean) American look much less informed than the typical (statistical median) American.

I’d note that the numbers in here for “actual” are also a bit suspect for some categories.

For example the percentage bisexual - a study showed about 10% of american men and 20% of american women have had bisexual attractions - which would indicate a real number being somewhere in the 15% realm.

It can be misleading if the results are presented like total for any person who had bisexual attraction, like I would say this does.

They think 30% of the nation live in texas, another 30 in NY and another 30 in california?

I’m sure it’s more around 5% being trans since there are people still in the closet or just not reported

They think 26% of people have a household income over 500k? Wtf?