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How Random Sampling is Helpful in Your Research

Random Sampling

The primary purpose of any research is to check the effectiveness of the topic selected. After selecting the topic, you conduct research on it. Collecting relevant data is another important task in this context. A wide range of credible sources help you to in completing a literature review. The next important step in your research work is explaining how you collected the data through random sampling. You’ll have to explain the tool for testing your sample, and interpreting the results as well.

Random sampling is a sampling method that helps in the research work. It is one of the most simple, and popular methods of data collection. As a researcher, you might have different samples. Each sample has an equal opportunity for being selected. This way, selected sample presents the whole population in the research. This sampling method helps you in several different ways. It helps the researcher in avoiding biasness within his research work as well.

This article aims to discuss how random sampling helps in the research work for your masters dissertation. This article will also discuss how it helps in drafting a good piece of writing. So let’s discuss these aspects in detail;

Types of Random Sampling:

Before going into details, let’s discuss the types of random sampling. There are four major types, and those are as follows;

Simple Random Sampling:

It is the first type of random sampling technique. In this type, the researcher selects a random sample from a small proportion of the population. Every member of the population has an equal opportunity of getting selected. This is one of the simplest, and most convenient methods of data collection. It may sound easy to select a sample while using this technique. But it’s difficult to use this technique in both surveys, and experiments. When a researcher has a small sample for his research, it increases the chances of biasness too.

Systematic Sampling:

Systematic sampling is another type of random sampling. In this type, a researcher chooses specific people as a sample from the population. He follows predetermined intervals (k) for selecting a sample. Then the researcher divides the population (N) by desired sample size (n) to calculate the interval. This sampling method is less complicated as compared to the previous one.

Stratified Sampling:

Stratified sampling is the third type of random sampling. This type of sampling divides the population into subclasses, or sub-groups. The name of these subclasses or sub-groups is strata. A researcher forms strata based on attributes, or characteristics. These attributes can be that of age, gender, and ethnicity. There are two other names for this sampling method. Those names are proportional, or quota random sampling.

Cluster Sampling:

This type of sampling method is similar to the stratified sampling technique. Cluster sampling also divides the population into different sub-classes. But each sub-class, or sub-group has comparable characteristics. This way, a researcher makes subclasses of the entire population through random selection. It is the most popular sampling method for widely spread population-based studies.

How Does Random Sampling Help In Research?

There are several different ways through which random sampling helps a researcher. Let’s discuss them in detail;

Helps to Save Time:

Every research work has some limitations, and time is one of them. Collecting data for research work is the prime responsibility of every researcher. It takes a lot of time to collect desired data for research work. And the researcher might also fail to get valuable data when interacting with people for the first time. He has to invest more time, and effort for getting the desired information. But random sampling allows a researcher to collect information much faster. This method is much easier than interacting, and recording the responses of the whole population. He can test the sample first. Then later on, he can apply those results to the selected population.

Helps to Save Money:

Money is another major constraint that a researcher faces in his research work. He contacts a lot of people for collecting the data. He also has to travel daily to meet people who will increase the cost. Limited financial resources might lead him to compromise the quality of his paper in some situations. But random sampling helps him in avoiding this aspect. It is important to note that gathering information from a selected sample helps the researcher in saving time and money both. This way, he also avoids compromising the quality of his research work.

Helps in Collecting Richer Data:

Every researcher aims to collect richer data for the research work. But what is the criterion for collecting richer data regarding research work? Apart from this, how does this data help the researchers? There are several ways through which a researcher can collect valuable information. Opinion polls are the most common example in this regard. He can also consider using interviews, and surveys to collect information. But random sampling is one of the most effective ways of collecting richer data. This is because the researcher can then ask more questions from people selected in the sample. This way, he’ll be able to save time, and get desired information at the same time.

Helps to Avoid Biasness:

Another key goal of any research work is the production of valuable results. This way, a researcher concludes his work through effective means. It does not only help him in increasing his credibility, but in helping future researchers as well. But how does a researcher get unbiased information? The random sampling technique helps a researcher in this regard. This technique helps the researcher in enhancing the credibility of his work. Every sample has an equal opportunity to represent population in the research. There is no influence, or pressure on any member of the sample either through this aspect. Hence the presentation of original opinions always helps a researcher in avoiding biasness.


This article discussed random sampling and how it helps in the aspect of research work. It is a sampling technique through which every sample has an equal opportunity of being selected. Meeting everyone, and recording responses is not an easy task. But with the help of this technique, a researcher gets desired information. The four different types of this sampling technique have also been discussed within this article. Those types include simple, systematic, stratified, and cluster sampling. In several ways, it helps a researcher, with for example avoiding of biasness. It helps him in saving time, money, and get richer data for the research as well. Using this data ultimately helps him produce a good piece of writing.

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