Sampling is the process of selecting a few from a large group. The bigger group is the population and the smaller group that is selected is sample. Sample, therefore, is a part of the population or the large group from which it is taken.
Take an example you want to know the average age of the students in a class. There are two ways to do this. You either ask each student their age and then sum them up and divide them by the number of students and in this way you get the average age of the students in the class. This method can be very time consuming and at times impossible to do. Another way to do this is to ask few students their age and sum them up and divide them by the number of the students and you get the average age of the students in the class. This method will be easier and convenient and can be used even if the number of students is too large.
Take another example you want to take a poll about a TV programme. You can submit a questionnaire or ask all the viewers who watch that programme to know their opinion. This can be daunting and at times very impractical. The better way can be to ask a few people and generalize their opinion to all the people who watch that programme.
Sampling makes research possible
Without sampling you cannot continue some studies, especially where the population is too large and widespread. Suppose you are conducting research on the consumption of electricity in an area, you cannot reach every household to know how much and how they use electricity in their houses. You can take sample and ask them and get results. Hence we can say that sampling makes every research possible.
Sampling saves human and nonhuman resources
Your time, energy and money everything is easy to manage when you take a sample rather than studying the whole population. This is important because in most of the studies you have a limited time and you have to find out the results during this time. When your research takes too much time it becomes obsolete till you are able to implement its findings. Its always better to be done on time.
Disadvantages of sampling
Sample may not be fully representative of the population
In any way there will be difference between population mean and sample statistics. This is called as sampling error. There are always chances of error and this error should not be high. A small error is expected and 0.05 or 0.02 percent error is thought to be acceptable but there should not be greater error. There are several ways to find out how much confidence we can place on our sample.
Sampling is a trade-off between gain and loss but you cannot take on your study without sampling. The researcher should ensure that the sample is free of biases and it is highly representative of the population.
How to make the sample most representable
One of the most important factor in determining the accurateness of the sample statistics is the sample size. Your sample should be enough large to represent the population. In a large population a small sample cannot yield accurate results.
Variation in the population
When the population is highly varied the selection of sample becomes difficult. In this case the population is divided into groups and from these groups small subgroups are selected as sample. The more varied the population is the more groups and subgroups are drawn before the final sample is taken.