What is a population in statistics?
In statistics, a population is the unity of events or participants in which a researcher is interested, for example all children of twelve years in a country.
Definitions and explanations of relevant terminology generally associated with statistical samples
In statistics, a population is the unity of events or participants in which a researcher is interested, for example all children of twelve years in a country.
In statistics, a sample is a number of participants or observations from the full population, which are being measured. A random sample is preferred. This means that all participants from the population have an equal chance of being selected for the sample
...A sample is random when all participants from the population have an equal chance of being selected for the sample.
A sample is representative if a certain characteristic occurs as frequently in the sample as in the population.
With simple random sampling, a sample is chosen in such a way that each possible sample has an equal chance of being selected from the population. When a researcher for example wants to select a sample of 100 participants from a population of 5000 participants and
...When it is difficult to receive information beforehand about how many and which participants are present in the population, the cluster sampling method is used frequently. Here, the researcher does not draw individuals from the population, but clusters of possible
...A convenience sample is a sample in which researchers use participants that are directly available. A main advantage of a convenience sample is that by using this method it is much easier to recruit participants than it would be with representative samples.
(Note:
...With a quota sample, the researcher determines beforehand what percentages should be met. The sample is drawn based on these percentages. For example, a researcher might say that he wants to select exactly 20 men and 20 women for his study instead of randomly drawing 40
...With a purposive sample, the researchers have strong ideas about which participants are typical for the population. Based on these ideas, they select which participants may participate in their study. The problem with purposive sampling is that it is highly subjective.
...It is difficult to make a fully representative sample. There are different ways in which a sample can not be representative. These are called sampling errors or bias, and may result in misleading research outcomes. Sampling errors (bias
...Non-systematic bias always occurs. These are the result of sampling variance. For example, psychology students from one year are not the same as psychology students from another year, which may result in a different mean of the measured variable
...Systematic bias is sampling error that stems from the way in which the research is conducted and can therefore be controled by the researcher. There are three types:
Selection bias: The way in which the
A large sample is not a guarantee for a representative sample. The way in which the sample is drawn is at least as important as the sample size. However, there are guidelines that tell you how large your sample at least should be. In general, it
...As mentioned before, you can never be sure that your results are exactly in accordance with the true population parameter. To indicate this, you can calculate a confidence interval. That is a range of numbers below and above the
...A statistical sample is a limited number of observations selected from a population on a systematic or random basis, which yield generalizations about the population after it is manipulated mathematically.
Add new contribution