ABSTRACT
A universal set of samples can be described as a population which consists of samples in set theory. A sample population can be sampled from a population which usually has a huge number of samples – more than 104. The sample population is applied to investigate the probabilistic properties of population in the inferential statistics. There are several methods to use for sampling from the population to get a sample population, for example, random sampling, and systematic sampling. The probabilistic results obtained from the sample population are used to estimate the properties of the population in the inferential statistics by means of testing of hypotheses, confidence intervals, regression method, etc. The properties of random variables can be estimated by the probability distribution which can be expressed by the probability mass function for the discrete sample space, and the probability density function for the continuous sample space, respectively.
