Sampling methods in research
Sampling methods in research work used to collect information from larger population in short time duration. Sampling methods in research is a technique used for collecting individual information or set of information from larger population to make measurements in research work.
11 type of sampling methods in research work used namely simple random sampling method, quota sampling methods, cluster sampling methods, systematic sampling methods, stratified sampling methods, convenience sampling methods, snowball sampling methods, multistage sampling methods, probability sampling methods and non probability sampling methods.
You decided to do research on larger population, then it's becomes very difficult for you to make collection of sample from each and every people of population. To overcome this large size population, researchers applied various types of sampling methods to collect sample and cover whole population by taking sample.
You can use sampling techniques to identify and select group of individuals or small sets of group of population. Sampling techniques help you in study whole population characteristics by taking small sets or groups of individual.
You can use sampling techniques to identify and select group of individuals or small sets of group of population. Sampling techniques help you in study whole population characteristics by taking small sets or groups of individual.
Sample vs population
Do you know? What are key differences between population and sample. Before starting sampling procedure you must able to find out key differences between population vs sample.
Population means collection of whole individual present in the entire group.
Sample means specific sets of group you are going to take sample and make study to derive conclusion from it's result.
What is sampling methods
Researchers applied two types of sampling methods namely probability sampling methods and non probability sampling methods during collection of sample. Sampling methods means those methodology used by researchers at the time of collecting sample from population of selected study area.
Here sampling methodology including various types of sampling techniques and tools which are used at time of gathering sample.
Why sampling used in research?
Various types of sampling methods are used for making larger population study area more easily. Sampling methods provides various types of tools to researchers to make his study to cover larger population of an area.
Main reason behind why sampling used in research are explained in this section of articles.
Sampling techniques used in research when study area of research huge and include large number of individuals. In that case sampling used in research.
What is Sampling
Sampling can be defined as collection of data from various sources available inside selected study area of the population.
Inside sampling researchers pick up small sets of individual by applying various types of sampling techniques according to his research purpose. These small sets of individual which are included in sampling considered as representative of whole population.
At the time of collection of sample researcher must be very careful in selecting how will he going to collect sample. It will be become very important for researcher to applied correct methods of sampling for derive suitable conclusion.
Examples of sampling
Suppose any fertilizer company wants to know about his company product performance on farming population of accross the country. You also know that it will be very hard task to involve each and everyone from the large farming population. Researcher will select small sets of individual group from all demographic area accross the country. Individual selected for taking participation in sampling will be representative of whole farming population of the country (selected study area).
Why every one from population not involved in sampling?
Every one not involved in sampling main reason behind that there larger number. Whole population included larger number of individuals and these larger number of individual make sampling procedure more complex, hard to manage sampling activities, huge human resource required, very cost expenditures and huge time will spend on collection of sample.
Types of sampling methods with examples
Do you planning to collect sample? So it's become important to choose correct methods of sampling collection, to derive correct conclusion after calculation of sample.
Researcher (you) uses two types of sampling methods in his research work.
- Probability sampling
- Non-probability sampling
Probability sampling method
In probability sampling method researcher (you) performed collection of sample by following sequence. Researchers in this sampling type of fix some rules, criteria and choose the population randomly.
You can collect sample efficiently according to probability theory. Probability sampling give to freedom to select sample freely from large population. In probability sampling there is equal chance to everyone to get in included in sampling.
Examples of probability sample method
Suppose you have to take sample of wheat crop sample from 20000 farm field. So here we had studied probability definition in mathematics.
From 20000 farm field number chance of involving every farm field in sampling is 1/20000 researcher collect sample randomly from 20000 farm field.
Types of probability sampling
There are four main types of probability sampling techniques used by researcher are given below:-
- Simple random sampling methods
- Cluster sampling methods
- Systematic sampling methods
- Stratified sampling methods
Simple random sampling
You can collect sample with the help simple random sampling. Simple random sampling one of the important type of probability sampling.
Simple random sampling technique will help you to gather sample randomly in simple way. Researcher are free to take sample from larger population randomly according to his research work.
Researcher considered this type of sampling method more reliable. In this type of sampling method there is equal chance to everyone to involve in sampling study. Simple random sampling considered biased free.
Example of simple random sampling
Suppose you are chairman of your university and you want to check students general knowledge of your university students.
Now you put all students name written on chit and put inside bowl.
Each student of university have equal opportunity to get involved in simple random sampling.
Cluster sampling
In the cluster sampling you can collect sample by making small from larger population. Cluster sampling is one of the important type of probability sampling. Researcher in this type of sampling divide whole population in small sets of group. From the name cluster is clear that making small group sets from larger size.
You can make whole population size in various type of clusters on the basis of age, colour, size, demographic area and many more.
Example of cluster sampling
Suppose Indian central government wants to know the exact number of foreigners are living inside India main land.
Now central government make India whole geographical structure form like Delhi, Madhya Pradesh, Mumbai and etc. After making whole geography of India India, then it will divide whole population into small group of cluster. Now it will become easier for government of India to collect sample.
Systematic sampling
In systematic sampling method researcher collect sample efficiently from population in systematic manner. Systematic sampling help researcher to take sample easily in equal interval of time.
Systematic sampling schedule on advance it get fixed by researcher. Path of systematic sampling predetermined by researcher. This type of probability sampling method considered as cheapest way of doing sampling.
Example of systematic sampling
Suppose you have to collect water sample number of 600 from 6000 water source. Now you will give numbering to each water source 1 to 6000.
You include every 10th number coming in water source selected (6000/600= 10).
Stratified sampling
Researchers in this type of sampling divide whole population size into smaller number of sets of groups.
These smaller number of groups never overlap with eachother and then represent same characteristics of population.
Examples of stratified sampling
Suppose you want launch a new product according to focusing different income groups of people living in the country.
In this case you will stratified sampling method. In this type of sampling you will divide all income group of population into different range of income.
After doing classification of income group population of the country. You can derive conclusion of different income earning people characteristics. Stratified sampling help researcher to decide which income group you can target according to the your product and whom you can eliminate from your sampling study.
Importance of probability sampling methods
There are many uses of probability sampling are given below:-
Eliminate sampling bias
Probability sampling eliminate chance of getting biased at time of collecting sample. Probability sampling give each individual of population chance to become participants in sampling study and represent whole population.
Samples which are collected by researcher with an application of probability sampling methods are of high quality. Sample collect in type of sampling are considered as high quality.
Individual diversity in population
As you that population included large number of diverse quality of individual. So it's become important to increase adequate representation of population in sample. To increase adequate representation probability help a lot. Individual included in probability sampling consists characteristics of whole population.
Accurate data
Researchers able to collect high quality sample. High quality sample helpful for researcher to derive accurate results and efficiency of accurate data increased.
Non-probability sample
Non-probability sample totally dependent on researcher capabilities and sentiment. Researcher make selection of individual his sample randomly. No any type of fixed methods of sampling followed by researcher. Equal opportunity not provided to each individual to take part in sample study.
Almost everytime time non-probability sample method used gives skewed result.
Non probability sampling can become useful where there is cost constraints or very less cost available for doing research.
Data collection done by non-probability sampling methods are not considered as high quality.
Non-probability sampling are cheaper in comparison to probability sampling methods. There might be be sample collection influence by biased.
You can use non-probability sampling methods when you doing exploratory and qualitative research.
In non-probability sampling used in research when researcher wants to make understanding for under researched population or smaller population.