Types Of Sample Methods And Techniques In Research

The main objective of any statistical or marketing is to obtain good results that are reliable for decision making. That is why we have to know the different types of sampling methods and techniques. Sampling methods and techniques play an important role in statistics and research methodology. 

Making the research with the wrong sample method will almost make you get misleading results. Knowing our sample method is one of the key factors to consider if your findings are accurate or not. 

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What is Sampling?

Sampling is a statistical method whereby researchers select the type of the sample. The important point here is to select a good sample from the other types. However, in sample methods and techniques, instead of studying and observing each unit in the universe, assuming that it represents the entire population, only part is studied.

The concept of sampling is also known as the methodology of drawing inference of the universe from random sampling. This theory deals with,

  1. Statistical Estimation
  2. Testing with Hypothesis
  3. Statistical Inferences

Statistical Estimation

The main objective of sampling is to estimate the value of unknown parameters. The two types of estimate are interval estimate and point estimate. Interval estimate has two limits i.e. lower limit and upper limit which the parameter value may lie. On the other hand, a point estimate is a single estimate in the form of a single number.

Testing of Hypothesis

The second objective of the sampling theory is the rejecting or accepting a hypothesis. Testing of Hypothesis leads us to decide whether an observation obtained in sampling has happened due to the fluctuations or the real one in sampling.

Statistical Inference

Indeed, Statistical Inferences helps in making a generalisation about population and determining the accuracy of such generalisation.

Features of Sampling Method

The main features of sampling method can be best describe as follows;

  • Reliability and Accuracy
  • Less time required and money
  • Greater suitability and Scientific base
  • Respondent Cooperation
  • Depth study and Detailed 

Characteristics of Sampling

For accurate and reliable conclusions from the research, it is very crucial that the selected sample has certain qualities. These qualities list below;

  • An ideal sample must represent the characteristics of the entire population.
  • Sample should not depend on other theory sample
  • Selection of sample should be sufficient
  • The sample selected should be the same
  • Process of sampling should economical
  • Sample should be simple and practical

What are the sampling methods or Sampling Techniques?

In statistics, the sampling method or technique is the process of studying the population by collecting information and analysing that data collected.

There are different types of sampling methods and techniques available, and they can subdivide into two categories. All these methods of sampling may involve mainly targeting hard or approach to reach groups.

Types of Sampling Method

In Statistics, there are other different sampling methods and techniques allocated to get accurate results from the population. There are two different groups of sampling. Namely:

  1. Probability sampling
  2. Non probability sampling

Probability Sampling

In probability sampling, the method uses some form of random selection. In this method, all those qualified individuals have a chance of selecting the sample from the other sample methods. Probability sampling method is very expensive and requires a lot more time than the non probability sampling method. The benefit of the probability sampling method is that it guarantees the sample to be representative of the population.

Probability sampling method is further divide into different types, such as clustered sampling, simple random sampling, stratified sampling, and system sampling. Let’s talk about the different types of probability sampling methods.

Clustered Sampling

In the clustered sampling method, the group or cluster of people are formed from the population scheme. The group has identical significatory features. Again, the cluster has the same chance of being part of the sample. Clustered method uses random sampling for the cluster of population.

Simple Random Sampling

Since the item selection mainly depends on the chance, this method is known to be as “Method of chance of selection”. As the item is randomly chosen, and the sample size is large, it is called “Representative Sampling”. In the sample random sampling, any item in the population has the same chance of being chosen in the sample.

Stratified Sampling

The total population divides into smaller sizes to complete the sampling process in the stratified sampling. After dividing the population into smaller sizes, the statisticians randomly chose the sample. The sizes divided are formed based on a few features in the population.

System Sampling

System sampling is calculated by dividing the total population size by the desired population size. The item chosen from the target population by choosing the random selection point and choosing the other methods after a fixed sample interval.

Non Probability Sampling

In this method, not all the members of the population have the chance to be part of the study of the sample method as compared to the probability sampling. The non probability sampling method is a technique in which the researcher chose the sample based on subjective judgement rather than the random selection.

Non probability sample methods are further divide into different types. They are as follows; consecutive sampling, snowball sampling, convenience sampling, judgmental sampling, and quota sampling. In this blog, we will discuss in detail all  the types of non probability.

Consecutive Sampling

Consecutive sampling is similar to convenience sampling with a slight difference. Here, the researcher picks a group of people or a single person for sampling. The researcher researches for some time to analyse the data and move to another group when needed.

Snowball Sampling

In addition, this is also known as a chain referral sampling method. In this method, the sample has traits that are difficult to obtain. With this, every identify member of a population is asked to find the other sampling units. Those sample units belong to the same targeted population.

Convenience Sampling

In a convenience method, the samples are chosen from the population directly due to the convenience availability for the researcher. Moreover, the samples are very easy to choose, and the researcher did not select the sample that outlines the entire population.

Judgmental Sampling

Judgmental sampling is also known as authoritative or purposive sampling. In judgmental the selected sample is based on the knowledge of the researcher. However, the chance of getting accurate results with minimum marginal error is creating the sample with instrumental knowledge.

Quota Sampling

In this method, the researcher selects the sample subsets that can bring the useful collection of data that generalised the entire population. In quota sampling, the researcher creates a sample that consists of the individuals to present the population based on a particular trait or quality.


All these are sampling methods. As a researcher, you have to know these sampling techniques and methods before trying to accumulate sample data. Data Scientist does a broad analysis of the results and therefore these methods can be used to help them to know insights of the data sample and its effect.

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