Population versus Sample
Imagine this, you (as a researcher) have been tasked by a large marketing company in your country to find the average income of all their customers to help them formulate new marketing strategies to enrich consumer preference and interests. The right way of doing this is to collect data on all their income and then divide it by the total number of customers.
Average Income $=\displaystyle\frac{\text{Total income of all the customers}{\text{Total number of customer}$
This looks impossible right? Yes, especially when data must be obtained from over millions of customers scattered all over the country. Since you can’t gather data on all these customers, it is advisable you collect data from a subset of the customers. This subset is known as a sample and all the customers in the country are called Population. The researcher must carefully select this sample using some assumptions:
- the sample selected is directly from the target population (customers of the marketing company)
- the customers are selected randomly
- a valid sample size is selected so as to make generalization to the entire population of customers
There may be errors in the data collection process, you need to account for them when writing your report.