What Are The Advantages And Disadvantages Of Random Sampling?

There are number of advantages and disadvantages of random sampling, and indeed, many types of random sampling itself. The first type of random sampling is a simple technique, which samples the whole population. The advantage of this technique is that if all those asked provide a sample then the answers provided will be highly representative. The disadvantages of this type of sample is that it is uneconomical to achieve, and also that the timescale to get the results would be too long.

A stratified random sample would sample people from individual groups that were identifiable. The advantage of this would be that it would be easy to make sure that all relevant groups were sampled. However, it would be highly costly and time-consuming in that the specific roles would first need to be established.

Cluster sampling is when small amounts of people are chosen to provide information. People would feel comfortable in providing this information, as it would be given as a group although statistics would be likely to be unnatural in that some areas would have higher levels of crime or unemployment for example.

A stage random sample would contain elements of all those types already mentioned and the advantage of this technique would be that a probability sample could be established at stages throughout. This would, however, be a very complex way of sampling and again would take a lot of time and be costly.

The other types of sampling are not random. Purposive sampling, which would pick subjects out dependent on what the sample was for would ensure the balance of the groups was correct if groups were being selected. Quota sampling would simply pick the required number of people and snowball sampling could include subjects who had particular traits.

Sampling that asks for volunteers is probably the least expensive way of sampling, although this can lead to inaccurate information.

Advantages:
-It's unbiased
-The method is fair

Disadvantages:
-This method is more time consuming than non-representative methods.
-Expensive
-Each person has to be located and questioned

It can be vulnerable to sampling error because the randomness of the selection may result in a sample that doesn't reflect the makeup of the population. Also, it may be cumbersome and tedious when sampling from an unusually large target population.

Randomness of selection could affect results.
Difficult with a large target of population.

In random sampling, researchers draw a sample from the population randomly so that every element in the population has an equal chance to be selected.  However, the assumption that 'randomly' walking upto people in a street produces a sample that is representative of the whole city is often wrong. For one thing,, any street, whether in a rich neighbourhood or a poor one, contains more of the same kinds of people than others. Secondly, Any researcher is apt to find some people more approachable than others, which is yet another bias. But then snowball sampling also has its disadvantages and random sampling definitely offers a considerable savings in time and expense.

Advantages
Totally unbiased
Represents the total population

Disadvantages
May not include sub sets
Bunching may occur

A primary disadvantage of random sampling is that it may not in fact be a random sample.   Therefore conclusions or interpretations of the sample data could be misleading and the consequences severe, such as death.   For example, a random sample of 100 individuals with cancer are selected to test a new cancer fighting drug.    The results of those sampled indicate the drug did reduce the risks of the cancer and in some cases the cancer went into remission.    However, if this drug were put on the market to treat 1,000,000 people with this particular cancer the side effect of "instant death" that did not appear in the original sample of 100 because none of the original 100 died would make this drug unacceptable if the sample had identified this fact.   Lets say the death rate was only 1% this would mean 10,000 people out of the 1,000,000 if treated with the new medicine would die instantly.  

Random sampling also could create costly repairs or expose individuals to dangerous situations.   For example, recall notices from automobile manufacturers are common place today, however, if full or first article testing were done instead of sample testing some of these recalls would be unnecessary.   The cost of recalls could well exceed the cost of full sampling in these situations.  

Complete disadvantages of random sampling

The advantages are that it is a straightforward and probably the simplest method of a sampling technique known as probability sampling. It attempts to ensure that the sample is random and thus representative enough the make generalisations about the whole population. However it is subject the sampling bias and sampling error

A simple random sampling of n=2070 farms,is taken from population N=20700,data collected on number of cattle per farm y on each farm.total y=25881,total  y(squared)=599486.estimate average no of cattle per farm, total number of cattle in the population,coefficient of variations of the estimates

Valid measure

It is fast and easy method to use

There is never a truly random sample, as if somebody tries to sample a population completely randomly you may ask the same qustion to the same person 3000 times, therefore your sample has failed. This happens because a random sample must choose everybody inside the sample AT THE SAME TIME!

Its expensive