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Disadvantage of Sampling through few Sampling methods: 1. cluster sampling
Higher sampling error, which can be expressed in the so-called "design effect", the ratio between the number of subjects in the cluster study and the number of subjects in an equally reliable, randomly sampled unclustered study. 2. Probability Sampling: * Requires that you have a list of all sample elements * More time-consuming * More costly * No advantage when small numbers of elements are to be chosen

3. Non-Probability Sampling * Greater risk of bias * May not be possible to generalize to program target population * Subjectivity can make it difficult to measure changes in indicators over time * No way to assess precision or reliability of data

DISADVANTAGE OF SAMPLING
The disadvantages of sampling are few, but important. The main disadvantages stem from risk, lack of representativeness, and insufficient sample size, each of which can cause errors. Inattention to any of these potential flaws will invalidate survey results.

DISADVANTAGES OF SAMPLING 1. Requires selection of relevant stratification variables which can be difficult. 2. Is not useful when there are no homogeneous subgroups. 3. Can be expensive to implement.

Disadvantages of Sampling through different sampling methods:

1. Simple random sample:
Disadvantages:
* Difficult to obtain * Due to its very randomness, "freak" results can sometimes be obtained that are not representative of the population. In addition, these freak results may be difficult to spot. Increasing the sample size is the best way to eradicate this problem. 2. Systematic Sample:
Disadvantages:
* Can introduce bias where the pattern used for the samples coincides with a pattern in the population. 3. Stratified Sampling:
Disadvantages:
* Nothing

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