In research, we deal with statistical data. And while dealing with statistical data, it becomes important to distinguish between 'population data set' and 'sample data set'.

In research, a population is the entire cluster that we want to draw conclusions about. On the other hand, a sample is the specific group (a sub-set of the population) that we practically reach out to.

For example, we want to know about political awareness among the university students of our country. Let us say, there are 10,0,000 university students in Bangladesh. Now, these 10,0,000 students are the population here. And clearly, it is not practical to reach out to every one of them for collecting necessary data. In that case, we need to go through proper methods and find out a sub-set from the population. If we separate 1,000 students from different universities and collect the data from them, then these 1,000 students are the sample here.

In such cases where the population cannot be reached to, conclusions are drawn from the data collected from that particular sample. And the process of finding a sample from a population is usually called 'sampling'.

So, it is obvious that the population is always larger than the sample taken for a particular study.