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Sampling Types

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  • A Sample is selected in such a way that each item or person in the population being studied has a known (non zero) likelihood of being included in the sample.
  • Not all items or people have a chance of being included in the sample. Results may be biased.

Simple Random Sampling

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  • Selection without any logic. All items in the population have an equal chance of being chosen in the sample.
  • For Example: Scientist randomly selecting people for researchpurpose.Other examples include:
    - Randomly selecting auto components coming out of a plant
    - Randomly selecting a telephonic conversation to check the quality of the conversation

Systematic Sampling

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  • When items are selected at the pre-determined interval when arrangedin an order
  • Example: Scientist selecting every 2 nd people for researchpurpose.Other examples include:
    - Quality Auditor selecting every 8th transaction as per the processing time
    - Selecting every 30th bottle coming out of the assembly line

Stratified Sampling

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  • When the population has different groups (strata). In stratified random sampling, independent samples are drawn from each group. The size of each sample is proportional to the relative size of the group
  • Example: Scientist randomly selecting people from each group categorized based on their designation for research purpose.

Cluster Sampling

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  • The population is broken down into many different clusters, and then clusters or subgroups are randomly selected.
  • Clusters can be of different ages, locations, people income, designation, etc.
  • For example: Scientist categorized samples into four subgroups based on their designation and selects doctors for the researchpurpose.

Judgmental Sampling

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  • Judgmental sampling is also known as purposive sampling.
  • Samples are selected based on the purpose or intention ofthe research.
  • The method is versatile enough to allow for the inclusion of items in the sample that are particularly important.
  • For example: Scientist selects associates wearing tie for researchpurpose as he intends to do it.

Convenience Sampling

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  • One of the easiest sampling methods is convenience sampling.
  • Samples selection is based on availability and selecting the samples that are convenient to the researcher.
  • For example: Scientist selects the people from various subgroups based on their availability for researchpurpose.

Quota Sampling

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  • It is similar to stratified sampling, we choose items based on predetermined characteristics of the population.
  • For example: Scientist selects all the women in a locality for research purpose. Other examples includes
    - Tax payers in the age range of 28 – 32 years in a region, etc. This is a way of collecting samples in a fast way but leaves space for bias.

Snowball Sampling

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  • Existing people are asked to nominate further people known to them so that the sample increases in size like a rolling snowball.
  • This method of sampling is effective when a sampling frame is difficult to identify. There is a significant risk of selection bias in snowball sampling, as the referenced individuals will share common traits with the person who recommends them.

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