This is a very broad question. I have included a link from the internet, but you can find many other links by searching under sampling methods.
Usually the question is:
What makes a sample's statistics be an accurate representation of the population?
No sample is a perfect representation of the population, but some samples are more representative than others.
If you are conducting a survey, you should make sure that the results are unbiased. For example, if you are asking people if they like to excersize, you should not do this at your local health club and then claim your sample represents everyone in your community.
Your sample should contain enough data. Sometimes, important surveys require hundreds or thousands of interviews. Asking a few people questions is not a good way to collect a sample.
There should be a plan to your collection of data, that is well documented. Sometimes, it is necessary to have a professional outside group conduct the study, so a representative sample is gathered. The Gallup organization are very well known for conducting political surveys. You don't want someone to "pick and choose" his data to get a certain result.
These are just some ideas- you may find more in the related link.
The larger the sample of data collected leads to a more accurate conclusion.
The larger the sample size, the more accurate the test results.
Estimates based on the sample should become more accurate.
A cat stool sample should be fresh, ideally within 12 hours, for accurate testing and analysis.
A cat stool sample should be fresh, ideally collected within 24 hours, for accurate testing and analysis.
The larger the sample, the greater the accuracy, but in every case, the sample must be truly random.
I'm sorry, but I need more context about SAMPLE 10 to provide an accurate answer. Could you please specify what SAMPLE 10 refers to?
becuase it is more accurate.
By comparing the sample with a known mass
It's obviously not completely accurate. But the more people you include the more accurate it gets. Statisticians choose the sample size to be large enough for a fairly accurate representation.
because its faster and then when you use a sample you can easily make accurate predictions about what would/will happen next
(Apex Learning) A higher sample size gives more accurate results.