What is Sampling
Sampling and Sample
Sampling is the process of drawing sample of a desired size from the population. A sample is a specimen that is representative of the population from which it has been selected. A sample can be taken from a population for various end-uses: in statistics sample of data is taken to draw conclusion about the whole data set; in research sample is taken to draw conclusions about the population parameters; in medical science a sample of the drugs is tested to know its efficiency and side effects.
Sampling has benefits
Sample is taken for a variety of reasons, some benefits of sampling are as follows:
- A sample can help you save time as well as human and financial resources. Cost effective methods have to be used in research, medicine, statistics and other areas of study. Time is also limited and one has to draw the conclusions. Studying the whole population can be a lengthy process and often impractical too. The processing and analysis of the data in statistics can be made easier with sampling, on the other hand, the results of the research will take years and years to come out.
- Sampling makes the process of research and statistical studies flexible. Without sampling you cannot setup high aims in research.
- A sample also helps in getting the results faster, in many studies the results should be reached to the audience so that they can get benefits from the findings. For example in medical science the results of the experiments can help the humanity in many ways, taking too long time may offset the importance and the scope of that research.
- Sampling sometimes becomes more accurate and effective than the population because of the ease of processing data. The researcher cannot handle the data of entire population and accuracy becomes questionable.
Types of Sampling
Simple random sampling
Stratified random sampling
Read more on Sampling in Research
- Sampling Types in Research - Reading Craze
There are various sampling types in research but they are broadly categorized in to random and non-random sampling designs. The researcher can use a mixed-method sampling design.
- How to Calculate Sample Size in a Research - Reading Craze
One of the important step in sampling is to decide about the sample size from the population. The best way to do it is by using formula to calculate sample size.
Aims in Selecting a Sample
While good sample is a useful mean to accomplish a research, badly selected sample can ruin the entire research. The data has to be selected form the sample that you have drawn. Accuracy in sample selection is therefore crucial for the validity and reliability of your research.
In selecting a sample you should try to:
- The sample represents the population and it should have to be highly representative of the population.
- Consciously or unconsciously biases should never be introduced in the sample. The sample should cover the whole population and for this purpose the accurate sampling technique should be used.
- It should also be ensured that every unit in the population has an equal chance of being selected.
Dis-advantages of Sampling
Sampling is a trade-off between gains and loses. There are certain dis-advantages of sampling, regardless of these drawbacks sampling is still used in several fields.
- Sampling may not be representative of the population because sample is only a part of the population and not the population itself.
- Sampling increases the chances of bias in research due to more manipulation.
- In non-random sampling the degree of generalizability is highly questionable.
- Sample should have to be big enough to represent the population. Very small sample in proportion to the population cannot be representative of the population.
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- A sample is a specimen of the population
- It is used to study population parameters
- Sampling saves human and non-human resources
- Sample should have to be highly representative of the population
- biases should be avoided in sampling
- There are three types of sampling: random, non-random and mixed
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