There are clear advantages and disadvantages to using lineage extraction as a statistical sampling method when conducting a survey of the study population.
Lineage extraction: overview
Random sampling is simpler and easier than random sampling. It may also further facilitate coverage of a wide range of research areas. Lineage extraction, on the other hand, introduces any particular parameter into the data. This can cause certain patterns to appear over or under.
Phylogenetic extraction is popular with researchers because of its simplicity. Researchers generally assume that the results represent most normal populations unless random traits are disproportionately present in all “nth” data samples (this is unlikely). ).
First, the researcher chooses the starting integer that is the basis of the system. This number should be less than the overall population (for example, not every 500 yards to sample a 100-yard soccer field). After the number is selected, the researcher chooses the spacing or space between the samples in the population.
- Due to its simplicity, phylogenetic extraction is popular with researchers.
- Other advantages of this methodology include eliminating the phenomenon of clustered selection and reducing the likelihood of data pollution.
- Disadvantages include overrepresentation of certain patterns and increased risk of data manipulation.
Example of lineage extraction
Lineage extraction evenly distributes the selected data. For example, in a population of 10,000, statisticians may choose to sample every 100 people. The sampling interval can also be systematic, such as selecting one new sample every 12 hours.
Benefits of lineage extraction
The advantages of lineage extraction are as follows.
Easy to implement and understand
Lineage extraction is relatively easy to build, perform, compare, and understand. This is especially important for surveys and surveys that are run under tight budget constraints.
Process control and sensation
Systematic methods also provide researchers and statisticians with a sense of control and process. This can be particularly useful for studies using strict parameters or narrowly formed hypotheses, assuming that sampling is reasonably constructed to fit specific parameters.
Clustered selections have been eliminated
Cluster selection is a rare phenomenon in which randomly selected samples approach within a population and is excluded by lineage extraction. Random samples can only be addressed by increasing the number of samples or performing multiple surveys. These can be expensive alternatives.
Low risk factor
Perhaps the greatest strength of the systematic approach is its low-risk factor. The main potential drawback of the system is that it is clearly less likely to pollute the data.
Disadvantages of lineage extraction
This method of investigation also has its drawbacks.
Suppose you can determine the size of the population
The systematic method assumes that the size of the population is available or can be reasonably estimated. For example, a researcher wants to study the size of a rat in a particular area. If you do not know the number of rats, you cannot systematically choose the size of the starting point or spacing.
The need for natural randomness
The population should show a natural degree of randomness along the selected metric. If the population has a standardized pattern type, the risk of misselecting a very common case becomes more apparent.
As a simple hypothetical situation, consider a list of favorite breeds (intentionally or accidentally) where all even-numbered dogs on the list are small and all odd-numbered dogs are large. If the systematic sampler starts with the 4th dog and chooses an interval of 6 dogs, the study will skip the large dogs.
High risk of data manipulation
Researchers are at high risk of data manipulation by phylogenetic extraction because they may be able to build systems to increase the likelihood of achieving the desired results, rather than having random data generate representative answers. Become. The resulting statistics were unreliable.