**is less expensive and more quick**. It is more economical to observe clusters of units in a population than randomly selected units scattered over throughout the state. Cluster Sample permits each accumulation of large samples.

What are advantages of coal?

**what is the disadvantages of coal**.

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- It allows for research to be conducted with a reduced economy. …
- Cluster sampling reduces variability. …
- It is a more feasible approach. …
- Cluster sampling can be taken from multiple areas. …
- It offers the advantages of random sampling and stratified sampling.

Random samples are the best method of selecting your sample from the population of interest. The advantages are that your sample should represent the target population and eliminate sampling bias. **The disadvantage is that it is very difficult to achieve** (i.e. time, effort and money).

Advantages of sampling. Sampling **ensures convenience, collection of intensive and exhaustive data, suitability in limited resources and better rapport**.

Cluster sampling is **more time- and cost-efficient than other probability sampling methods**, particularly when it comes to large samples spread across a wide geographical area.

- High level of subjectivity.
- Research findings can never be 100% representative of population.
- The presence of group-level information is required.

Cluster sampling: **convenience and ease of use**. Simple random sampling: creates samples that are highly representative of the population. Stratified random sampling: creates strata or layers that are highly representative of strata or layers in the population.

These disadvantages include **the time needed to gather the full list of a specific population**, the capital necessary to retrieve and contact that list, and the bias that could occur when the sample set is not large enough to adequately represent the full population.

Simple random sample advantages include **ease of use and accuracy of representation**. No easier method exists to extract a research sample from a larger population than simple random sampling.

Advantages of Sample Surveys compared with Censuses: **Reduces cost – both in monetary terms and staffing requirements.** **Reduces time needed to collect and process the data and produce results as it requires a smaller scale of operation**. (Because of the above reasons) enables more detailed questions to be asked.

**Simple random sampling**: One of the best probability sampling techniques that helps in saving time and resources, is the Simple Random Sampling method. It is a reliable method of obtaining information where every single member of a population is chosen randomly, merely by chance.

Without modifying the estimated parameter, cluster sampling **is unbiased when the clusters are approximately the same size**. In this case, the parameter is computed by combining all the selected clusters.

The main difference between stratified sampling and cluster sampling is that with **cluster sampling, you have natural groups separating your population**. … In stratified sampling, a sample is drawn from each strata (using a random sampling method like simple random sampling or systematic sampling).

- The absence of systematic error and sampling bias.
- Higher level of reliability of research findings.
- Increased accuracy of sampling error estimation.
- The possibility to make inferences about the population.

**The results will always be more accurate than** non-probability sampling. It is possible to specify the probability of selecting any particular sample of a given size. Estimates are statistically projectable to the population. Sampling units are selected by chance as opposed to the judgement of the researcher.

What is the least reliable and least efficient probability sampling technique? **Cluster Sampling**. You just studied 41 terms!

What is the biggest barrier to using random sampling? a. It **is often unethical**. You should not have all participants have equal chances of being selected because some might not want to participate.

It is cheaper to collect data from a part of the whole population and is economically in advance. Greater Speed. Sampling **gives more time to researcher for data collection**, so it is quickly and has a lot of time for collection of inflammation. Detailed Information.

Basis for ComparisonCensusSamplingResultsReliable and accurateLess reliable and accurate, due to the margin of error in the data collected.

Explanation: Census method of data collection **is always better than the sample method** because; 1) The results obtained from census method is more accurate. 2) The census method is less time consuming.

Cluster sampling is **a probability sampling technique in which all population elements are categorized into mutually exclusive and exhaustive groups called clusters**. Clusters are selected for sampling, and all or some elements from selected clusters comprise the sample.

As with all probability sampling methods, **simple random sampling** allows the sampling error to be calculated and reduces selection bias. A specific advantage is that it is the most straightforward method of probability sampling.

Rationale: Although it is the most widely used approach for quantitative researchers, **convenience sampling** is the most vulnerable to sampling biases.

What is a major drawback to to cluster sampling? **each cluster tends to be more homogeneous in a variety of ways than the population as a whole**. which type of sampling is especially useful when attempting to locate participants who are harder to find?

When conducting a cluster sample, it is better to have fewer clusters with more individuals when **the clusters are heterogeneous**. True, because when the clusters are heterogeneous, they are scaled down versions of the population.

In short, it ensures each subgroup within the population receives proper representation within the sample. As a result, stratified random sampling **provides better coverage of the population since the researchers have control over the subgroups to ensure all of them are represented in the sampling**.

In cluster sampling, groups of elements that ideally speaking, are **heterogeneous in nature within group**, and are chosen randomly.

Cluster sampling is a **probability sampling technique** where researchers divide the population into multiple groups (clusters) for research. Researchers then select random groups with a simple random or systematic random sampling technique for data collection and data analysis.

The motivation behind using probability sampling is **to generate a sample that is representative of the population in which it was drawn**. Random sampling does not guarantee that every random sample perfectly represents the Page 2 23 population.