Simple Random Sampling

Introduction:

Simple random sampling is defined as the selection method of any population, where each member of the population has an equal chance of probability of getting selected. These simple random sampling can be compounded into a complex sampling method. It plays a vital role in representing the accuracy of the population. We come across several simple random sampling examples, in our daily life, for example, the lottery system is one of the general examples. Simple random sampling is very much beneficial in the financial and statistical field, as it is a reliable source of accurate information. Though, due to lack of carefulness sampling bias occurs.

Simple Random Sampling Definition:

Simple random sampling definition states that it is a kind of selection in which an individual or any item that is being selected is dependent upon the chance or the probability and each item or individual has an equal chance and probability of getting selected. Simple random sampling is one of the basic types of sampling, whereas it could be compounded into several complex sampling methods. Random sampling is termed unbiased selection as all individuals have an equal chance of getting selected and the average of these samples will represent the Accuracy of the population. The lottery system is one of the general simple random sampling examples. Overall, the simple random sampling definition states that it is the simplest form of the probability techniques of sampling.

Types Of Random Sampling:

Random sampling is termed as the selection of any individual randomly, as suggested by the name itself. There are four distinctive types of random sampling and they are:

1. Simple random sampling: This sampling category is termed as the selection of several individuals randomly. At the same time, a sampling frame is required to collect down the database of all the members, individuals or populations. Working on an Excel sheet is a great example of simple random sampling.
2. Stratified random sampling: As per the name, this category of random sampling is stratified, i.e., yes, election members are divided into two groups according to their abbreviations or attributes. After the division, the random sampling is done, which means the selection of any individual or population is made based on the divided groups so that each group gets an equal probability to represent itself.
3. Cluster random sampling: In cluster random sampling, the population is divided into different groups called clusters according to their attributes or abbreviations. Whereas each cluster represents its group and the selection is made among the clusters, i.e., the formed groups.
4. Systematic random sampling: This category of random sampling is systematic and organised. Therefore, the sampling or the selection of every nth individual is considered. For example, while taking a survey, only interviewing the 5th person walking by is considered systematic random sampling.

Simple Random Sampling Methods:

Simple random sampling is done in an organised way as well. The method of performing a simple random sampling is:

• Determine the population on which the study or the sampling must be performed. It must be ensured that every individual is taking part in the selection process to give them an equal chance of getting selected.
• The second step is to decide the sample size. If the sample size is larger, there will be more work, cost and statistical certainty.
• Now the selection process is carried out, which can be carried out by the method of lottery or by considering a random number. There is several software to perform the simple random sampling methods.
• The final method is simple random sampling is to collect the data and record them in the respective database.

There are a lot of chances that a number of the population might not take part in the selection process. This will lead to a sampling bias, which means that several participants will have more probability of getting selected.

Advantages Of Simple Random Sampling:

A simple random sampling is very beneficial to the financial system in the statistical field. Cell advantages of simple random sampling are:

• Simple random sampling is one of the appropriate selection methods. If it is carried out carefully, there will be no chances of bias.
• As there is no restriction to the sample size, simple random sampling can be done among the vast majority of the population.
• Simple random sampling does not require any skilled person or prior knowledge of any kind.
• Simple random sampling provides a way of learning and growing as the person achieves experience while sampling more and more populations.
• If Simple random sampling is done on a large scale, then the availability of the small size sampling becomes easier as it can be grabbed from the large-scale population.
• In simple random sampling, the data is collected and stored in the database, which is informative and easy to access.

Conclusion:

Simple random sampling is termed as the selection of the population randomly, where every member of the population has an equal chance of getting selected. Apart from simple random sampling, there are three other types of random sampling, namely, stratified random sampling, cluster random sampling and systematic random sampling. Whereas sometimes a situation occurs when several members do not participate in the selection process, leading to sampling bias. Sampling is termed as a fundamental method of collecting useful data. As simple random sampling in the selection process is based on probability and chances. It is required to have a basic knowledge of probability.