CEVAP:

The Oxford dictionary of statistical terms defines the sample as a part of a population, or a subset from
a set of units, which is provided by some process or other, usually by deliberate selection with the object of investigating the properties of the parent population or set. A good sample must represent or model the
population that the sample was taken. A representative sample includes similar distribution of important
characteristics (e.g., age, gender, marital status, health status) with the distributions of those characteristics
in the population. For example, if the population of interest includes the 10,000 workers in a factory,
where 70% of workers are male and 15% of workers are over 56 years of age. Clearly you can see that the
workers are not similar to each other, they have some distinct characteristics that define what a worker is,
in here, only two of those characteristics are shown. Therefore, if you want to take a random sample from
this population of workers, you would like to include the characteristics of the population in your sample
as much as possible. The main importance of a sample is the accuracy with which represent the target population including the people, institutions, buildings, patients, and systems to which or to whom the results obtained from
the sample are to be applied or generalized.