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 Description  
 Sample:  A selection from a population.

Usually we cannot collect data from every member of the population in which we are interested. We must find a sample that will accurately represent that population. We use the results of the sample to draw a conclusion about the population.

Here are some different types of samples:

biased sample: A sample that does not accurately represent the population. Biased samples can give inaccurate results. For example, if you wanted to know the percentage of students at your school who recycle, sampling from the ecology club would result in a biased sample.

convenience sample: A sample that is chosen because it is easy. For example, if you wanted to find out the percentage of students who ate the school lunch, and you just asked those people at your table if they ate the school lunch, then you would have a convenience sample.

random sample: A sample that accurately represents the whole population. For example, if you wanted to get a random sample of all the students in your school, you could put all of their names in a bin and randomly draw out as many as you wanted in your sample.

systematic sample: A sample that is chosen systematically. For example, if you surveyed every tenth person in a line, you would have a systematic sample.

voluntary-response sample: A sample you get when you ask for volunteers. For example, if you had a survey on the internet, then those who answered would do so voluntarily.