What is proportional allocation in stratified random sampling? Proportional allocation is a procedure for dividing a sample among the strata in a stratified sample survey. As a result, strata with large numbers of units in
What is proportional allocation in stratified random sampling?
Proportional allocation is a procedure for dividing a sample among the strata in a stratified sample survey. As a result, strata with large numbers of units in their populations receive more sample, whereas small strata receive less sample.
Does stratified sampling have to be proportional?
Now that the strata sample size is known, the researcher can perform simple random sampling in each stratum to select his survey participants. In a disproportional stratified sample, the size of each stratum is not proportional to its size in the population.
What is the difference between stratified random sampling and cluster sampling?
The main difference between stratified sampling and cluster sampling is that with cluster sampling, you have natural groups separating your population. With stratified random sampling, these breaks may not exist*, so you divide your target population into groups (more formally called “strata”).
Can cluster sampling be combined with stratified sampling?
Cluster sampling can be combined with stratified sampling, because a population can be divided in L strata and a cluster sample can be selected from each stratum. As in the case of ratio estimators we can consider separate estimators and combined estimators.
When stratified sampling is used?
Stratified sampling is used when the researcher wants to understand the existing relationship between two groups. The researcher can represent even the smallest sub-group in the population.
What are examples of cluster sampling?
An example of single-stage cluster sampling – An NGO wants to create a sample of girls across five neighboring towns to provide education. Using single-stage sampling, the NGO randomly selects towns (clusters) to form a sample and extend help to the girls deprived of education in those towns.
What is an example of cluster sampling?
How is sample size related to stratified sampling?
the sample size is directly proportional to N h and σ h, i.e., allocate a larger sample size to the larger and more variable stratum. the sample size is inversely proportional to c h, i.e., this allocates smaller sample sizes to the more expensive stratum. In order to use the optimal allocation, one must be able to estimate σ h
Which is better cluster sampling or random sampling?
Both methods divide a population into distinct groups (either clusters or stratums). Both methods tend to be quicker and more cost-effective ways of obtaining a sample from a population compared to a simple random sample. Cluster sampling divides a population into groups, then includes all members of some randomly chosen groups.
Which is the optimal allocation in sampling Stat?
The optimal allocation is: n h = (c − c 0) N h σ h / c h ∑ k = 1 L N k σ k c k
When is the cost of sampling the same for each stratum?
If the cost of sampling from each stratum is the same, then the optimal allocation (the allocation with the lowest variances) is: However, if the cost of sampling differs from stratum to stratum and the total cost is: where c 0 is the overhead cost, c h is the cost per unit for stratum h.