16 Amazing Pros and Cons of Random Sampling

Random sampling is a part of the sampling technique in which the sample has an equal probability of being chosen. Every element of the population has a known, non-zero probability of being selected.

The elements that compose the population are explicitly defined. There is a potential of every sample being enumerated. The probability of selecting any potential sample can be specified.

Pros and Cons of Random Sampling

Pros of Random Sampling

  1. It is simple

Individuals of the population are selected randomly hence the researcher does not go for a specific population to do the research hence it is simple for the research to be conducted as compared to other methods of doing research.

  1. There is no bias

There is no bias in random sampling as every member of the population has equal chances of being taken.

  1. The results can be applied to the entire population

The results can be used for a large population as there is no bias hence there is a possibility that the results can be what the whole population is.

  1. Easier to form sample groups

The groups that are intended to be used in sampling are easy to form and this may give the researcher an easy time studying a certain population.

  1. It requires little knowledge

The researcher needs little knowledge for him or her to conduct research on certain population hence it allows many people to conduct the research.

  1. There is an equal chance of selection

The members of the population are given equal chances to be selected. It is not specific on which population is to be used for the study.

  1. It has fewer errors

As the researcher is not specific about the population to conduct research on, there is a possibility of getting accurate results hence the best method to be used to conduct research.

  1. It is relatively efficient

The results got from random sampling are relatively efficient as compared to the results from other methods of research.

Read More: Pros and Cons of Qualitative Research 

Cons of Random Sampling

  1. The quality of the data is based on the quality of the researcher

When the data being collected is by face-to-face interviews, then it needs someone who knows how to collect the information from the field as poor research will not be able to give comprehensive results.

  1. Difficult when the population is too large

When the population is large, then the researcher should have bigger frames for him to capture the sample from a large area which can sometimes be inaccurate.

  1. It needs a large population

The population has to be large for the researcher to pick on the samples but if it is small then the researcher will have to conduct research on nearly the whole population.

  1. Easy to get wrong results

The members of the population used can have different features from the ones that are not used hence the results can easily be wrong.

  1. No guarantee that the results will be universal

As the members off the population are picked randomly, there is no guarantee that the results got will show the real features of the whole population.

  1. Complex and time-consuming

It takes a lot of time for the researcher to go to the field and collect samples to be studied on.

  1. It is relatively costly

The researcher will have to use some of his resources in order for him to conduct the research hence it can sometimes be costly.

  1. Not easy to utilize additional knowledge

The researcher is not allowed to utilize additional knowledge and this makes him to strictly perform the research using the variables given.

Read More: Pros and Cons of Bus Topology 


The random sampling method is the easiest way of conducting research as the researcher is only allowed to go to the field and collect the information about a certain population. Although the results cannot be effective at some time because the population that is being studied may have varied characteristics.

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