efficiency
Random sampling is picking a subject at random. Systematic sampling is using a pattern to pick subjects, I.e. picking every third person.
simple random sample is to select the sample in random method but systematic random sample is to select the sample in particular sequence (ie 1st 11th 21st 31st etc.)• Simple random sample requires that each individual is separately selected but systematic random sample does not selected separately.• In simple random sampling, for each k, each sample of size k has equal probability of being selected as a sample but it is not so in systematic random sampling.
Sampling error leads to random error. Sampling bias leads to systematic error.
avantages and disadvantages of mixed sampling are explained by example given below : if we want to take sample of trees in the forest of India for this we will selected the forests by the simple random sampling and after this we will selected the trees by the systematic sampling we can not used simple random sampling here due to not availability of frame of trees.So this is adavantages of mixed sampling. Now if we want to check the relability of whole procedure then we will not check it .So this is disadavantages of mixed sampling.
1) Simple random sampling 2) Systematic sampling 3) Stratified sampling 4) Cluster sampling 5) Probability proportional to size sampling 6) Matched random sampling 7) Quota sampling 8) Convenience sampling 9) Line-intercept sampling 10) Panel sampling
Hi, 1.The main advantage of Systematic sampling over simple random sampling is its simplicity. It allows the researchers to add a degree of system or process into the random selection of subjects. 2.Another advantage of systematic random sampling over simple random sampling is the assurance that the population will be evenly sampled. Disadvantage The process of selection can interact with a hidden periodic trait within the population.
Compare the efficiency of simple random sampling with systematic random sampling for estimating the population mean and give your comments.
Random sampling is picking a subject at random. Systematic sampling is using a pattern to pick subjects, I.e. picking every third person.
Simple Random Sample Stratified Random Sampling Cluster Sampling Systematic Sampling Convenience Sampling
They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.
Circular systematic sampling is a random sampling method. An example is random sampling of households. Assume that a random number generator provides the number 49 as a starting point. Starting with the household that is 49 on the target list, every nth household on the list would be sampled until the desired sample size is reached
simple random sample is to select the sample in random method but systematic random sample is to select the sample in particular sequence (ie 1st 11th 21st 31st etc.)• Simple random sample requires that each individual is separately selected but systematic random sample does not selected separately.• In simple random sampling, for each k, each sample of size k has equal probability of being selected as a sample but it is not so in systematic random sampling.
Stratified random sampling.
You can't conduct startified sampling if there are no difinative groups, thus systematic sampling is more efficient if your data has no groups.
It can interact with a hidden periodic trait within a population hence the technique will be compromised since there will not be random and representativeness of the saple
random sampling ,systematic sampling , self-selected , and there is one more i don't know
Sampling error leads to random error. Sampling bias leads to systematic error.