Because the whole population might be too large to sample.
A good example is the population of the world. At nearly 7 billion people, it would be unrealistic to sample each person to determine some factor that you are looking at. Generally, we sample a subset of the population, taking into account differences (or errors) that might result, in this case, regional and cultural, in order to estimate the behavior of the larger population.
large
A sample consists of a small portion of data when a population is taken from a large amount.
The sample must be large and random.
Assuming that the population was carefully defined, the sample population was carefully and correctly chosen, and that there were significant results, then the implication is that the results of the study, within the confidence limits indicated, hold true for the population at large.
its time consuming and expensive if its a large sample you need or a big target population
A sample! And the large group is called the population.
large
A sample consists of a small portion of data when a population is taken from a large amount.
The sample must be large and random.
Researchers are using a procedure known as simple random sampling. This involves selecting individuals at random, where every individual has an equal chance of being selected, to ensure the sample is representative of the population.
that you have a large variance in the population and/or your sample size is too small
The term is "representative sample." It is a subset of a population that accurately reflects the characteristics of the whole population it is meant to represent.
Span the full spectrum of a population's genetic variation. <apex> Reflects the genetic variation of a population...
A large trial is necessary to provide good sample that is representative of the population
span the full spectrum of a population's genetic variation.-apexI got you guysssss.feel free to hmu on snap king.youssof ( need knew friends ;--;)
The law of large numbers states that as the number of observations in a sample increases, the sample mean will tend to approach the population mean. In other words, the larger the sample size, the more accurate the estimate of the population parameter. This law forms the basis for statistical inference and hypothesis testing.
Yes, but that begs the question: how large should the sample size be?