The difference between a sample and a representative sample is that a representative sample is representative of a larger population and therefore includes more people in the sample than a sample that is just a sample of a larger population. A sample is usually not representative of the larger population, therefore it is important to be able to compare one set of data with another.
The general formula for a representative sample is P(N) = E / E = P(1) / E = N / N. If your sample is representative, then it is likely that your population is representative, therefore E = P(1)/N.
A representative sample is not representative of the larger population because the two sets of values aren’t related. E is usually the size of the population while P1 is usually the size of your sample. So PN P1E E are your population’s sample and its size is E. The number of people in your sample is N. So if the sample is N people, then it is a representative sample.
The problem is that people do not have the same type of memory they have, so it would be difficult to have a representative sample because you only have one of those individuals. If you have a population sample, you are probably not representative of the population at all.
We have a population sample of 1 million, so we are definitely representative of the population. We are not necessarily representative of the population as a whole. We may be biased toward those who have the same interests we do, or who have the same friends. If you have a sample that is over-represented, then you will not be representative at all.
We really don’t know what the population of the world is or what its population is, but we can estimate it by looking at the size of our sample. If we have a sample of 1 million, we are likely to be representative of the world population, but we are still not representative of the world population as a whole. Not a good indicator of the true population.
When you look at a sample of random people, you are likely to find that the most common answers are often “yes” and “no.” So if you want to test whether you have a large enough sample to have an accurate measure of the population, you should use a representative sample. An ideal representative sample would be a random sample of actual people.
The second thing we do need to be able to do is to make sure we are talking about a specific population. We’ll explore that next time, but remember that we should be talking about the real population, not just the random people on the Internet.
An ideal representative sample would be a random sample of actual people. The real population is the population of our country, but we’re not talking about a randomly selected sample. To draw a representative sample, we take a random sample of a population which we define as a subgroup of that larger population. So if we want to draw a representative sample of “dudes,” we take a random sample of “dudes.
We may not have a very large group of dudes, but we do have a much smaller group of women. That’s why the “representative” concept is important to us, because it’s a way to reduce the bias of our data.
