statistical.
random sampling
used for a smaller population
They have used Stratified Sample. Design because stratified sample is a sampling technique in which the researcher divided the entire target population into different subgroups, or strata, and then randomly selects the final subjects proportionally from the different strata. This type of sampling is used when the researcher wants to highlight specific subgroups within the population. So in this Research this technique is used by the researcher.
The sampling proportion may be used to scale up the results from a sample to that of the population. It is also used for designing stratified sampling.
it can be used when members of the population are heterogenous
random sampling
used for a smaller population
They have used Stratified Sample. Design because stratified sample is a sampling technique in which the researcher divided the entire target population into different subgroups, or strata, and then randomly selects the final subjects proportionally from the different strata. This type of sampling is used when the researcher wants to highlight specific subgroups within the population. So in this Research this technique is used by the researcher.
The lognormal distribution, probably.
The sampling proportion may be used to scale up the results from a sample to that of the population. It is also used for designing stratified sampling.
The sampling level is the size or limit of a population used during a study. This level is used to determine if a particular standard or mandate is being met.
it can be used when members of the population are heterogenous
Primary sampling is a research method used by various companies for many different reasons. The primary sampling unit arises in sampling surveys where population elements are grouped, and those groups becomes units in the sample selection.
In practice, systematic sampling is used on account of its simplicity and convenience. It's easy to explain to the people doing the actual work. It can be justified theoretically wherever the population from which units are to be sampled systematically are randomly distributed. It can be used for sampling households, sampling callers on a telephone line, sampling plants along a transect in (say) a field, sampling people passing through customs, and so on.
It involves selection of a certain number of sub-samples rather than one full sample from a population. All the sub-samples should be drawn using the same sampling technique and each is a self-contained and adequate sample of the population. Replicated sampling can be used with any basic sampling technique: simple or stratified, single or multi-stage or single or multiphase sampling. It provides a simple means of calculating the sampling error. It is practical. The replicated samples can throw light on variable non-sampling errors. But disadvantage is that it limits the amount of stratification that can be employed. IPS(interpenetrating sampling) provides a quick, simple, and effective way of estimating the variance of an estimator even in a complex survey. In fact, IPS is the foundation of modern resampling methods like Jackknife, bootstrap, and replication methods. In IPS, three basic principles of experimental designs, namely, randomization, replication, and local control, are used. IPS is used extensively not only in agriculture, but also in social sciences, demography, epidemiology, public health, and many other fields.
it is a method used in order to recognize suspected population status in compression with their factors
This type of sampling method is used when data is gathered by sampling individuals from a certain group. For example, a researcher may ask for a sample of 200 students from an ivy league school as a sample for their survey.