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Probability and Non-Probability Sampling

Probability sampling

In probability each unit of the population has known (non-zero) probability of being included in the sample and samples are selected randomly by using some random selection method. That’s why, probability sampling may also be called random sampling. In probability sampling reliability of the estimates can be determined. In probability sampling, samples are selected without any interest. The advantage of probability sampling is that it provides a valid estimates of sampling error. Probability sampling is widely used in various areas such as industry, agriculture, business sciences, etc.

Important types of probability sampling are

  • Simple Random Sampling
  • Stratified random sampling
  • Systematic sampling
  • Cluster sampling

Non-probability sampling

In non-probability sampling samples are selected by personal judgement due to this personal judgement in selection of sample bias may include which makes the result unrepresentative. Non-probability sampling may also be called as non-random sampling. The disadvantage of non-probability is that the reliability of the estimates cannot be determined.

Types of non-probability sampling are

  • Purposive sampling
  • Quota sampling
  • Judgement sampling
  • Snowball sampling
  • Convenience sampling

Differences between Probability and Non-Probability Sampling

The difference between non-probability and probability sampling is that non-probability sampling does not involve random selection of object while in probability sampling objects are selected by using some random selection method. In other words it means that non-probability samples aren’t representative of the population, but it is not necessary. But it may means that non-probability samples cannot depend upon the rationale of probability theory.

In general, researchers may prefer probabilistic or random sampling methods over a non-probabilistic sampling method, and consider them to be more accurate and rigorous.  However, in applied social sciences, for researchers there may be circumstances where it is not possible to obtain sampling using some probability sampling methods. Even practical or theoretically it may not be sensible to do random sampling. Therefore a wide range of non-probability sampling methods may be considered, in these circumstances.


Sampling Basics

It is often required to collect information from the data. There two methods for collecting the required information.

  • Complete information
  • Sampling

Complete Information

In this method the required information are collected from each and every individual of the population. This method is used when it is difficult to draw some conclusion (inference) about the population on the basis of sample information. This method is costly and time consuming. This method of getting data also called Complete Enumeration or Population Census.

Sampling

Sampling is the most commonly and wisely used method of collecting the information. In this method instead of studying the whole population only a small part of population is selected and studied and result is applied to the whole population. For example, a cotton dealer picked up a small quantity of cotton from different bale in order to know the quality of the cotton.

Purpose or objective of sampling

Two basic purposes of sampling are

  1. To obtain the maximum information about the population without examining each and every unit of the population.
  2. To find the reliability of the estimates derived from the sample, which can be done by computing standard error of the statistic.

Advantages of sampling over complete enumeration

  1. It is much cheaper method to collect the required information from sample as compare to complete enumeration as lesser units are studied in sample rather than population.
  2. From sample, the data can be collected more quickly and save time a lot.
  3. Planning for sample survey can be done more carefully and easily as compare to complete enumeration.
  4. Sampling is the only available method of collecting the required information when the population object/ subject or individual in population are of destructive nature.
  5. Sampling is the only available method of collecting the required information when the population is infinite or large enough.
  6. The most important advantage of sampling is that it provides reliability of the estimates.
  7. Sampling is extensively used to obtain some of the census information.

For further reading visit: Sampling Theory and Reasons to Sample


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