By a small sample, we may judge the whole pic!
All of us might have used the concept of sampling in our routine life. For instance, while purchasing vegetables from a shop market, don’t we examine a few to assess the quality of the whole lot? Doesn’t a doctor examine a few drops of blood as a sample in order to draw conclusions about the blood constitution of the entire body? Most of the time while dealing with big data problems, it’s not feasible to collect data from the whole population. Thus, sampling techniques are a useful procedure for selecting a subgroup (i.e., sample) from a population that is expected to be a representative of the whole population, in turn saving the time, cost as well as the efforts needed in examining the complete data. If anything goes wrong with the sample of data, then it will be directly reflected in the final result.