A *random* sample asks 1,000 people picked at random the same questions.
A *representative* sample asks 1,000 people picked according to a data filter the same questions. So e.g 51% of Americans are women then you will want to include 510 women if your survey. If 20% of women voted Republican in the last election then you’ll want 102 women in your survey who vote Republican.
Preparing and optimising sets of people for surveys is a part of statistical analysis , there are lots of methods to identify groups and subgroups within a large population, and of course ways that survey results can be skewed to give a result before the question is even asked (99% of people surveyed ( ^at ^a ^gun ^convention) say they’re in favour of looser gun controls). Numbers don’t lie, but statistics can be fudged and misrepresented very easily, which is why random surveys (and even more structured ones with a low sample size) shouldn’t be taken at face value as indicative of a majority opinion.
Latest Answers