The question appears to have some confusion. The groups within a populations are not always fixed. A population may be divided in different groups in several alternate ways. It is for the researcher to decide if there is a need to identify these groups separately, and if so, what criteria is to be used for grouping.
However, assuming that there is a need to divide the population in groups, it should be done in such a way that the variation within the group is minimized while that between the group may be high. The question assumes the reverse regarding variation within and between the group.
Having clarified this issue, I will get down to answering the question of appropriate method of sampling for different groups within a population. There are two basic method of sampling - random and systematic. What method is appropriate in a given situation is not really dependent on the nature of groups within a population. Only requirement is that the method should be common for all the groups within the population.
Another aspect of sample selection whether the total sample is to be drawn from the complete population without differentiating between group, or to draw sample from each group separately. The First method is appropriate when differences between the groups is not high, or when it is not necessary to analyse data group wise.
It is best to draw sample form each group separately when, it is important to to do detailed analysis of each group separately, or when there is high variation between groups. When this is the selected method, then the additional question of sample size for each group need to be answered. There are three possible methods for this. First alternative is to take equal number of samples from each group. This method is appropriate when the size of each group is large and variation within groups is comparable, and sample size is decided based on desired level of accuracy and confidence.
Second method is to decide sample size separately for each group based on variation within each group - higher the variation, larger the group. This method is appropriate when the variation within groups differ from group to group. Third method is to have have sample size proportional to the group size. This method is appropriate when size of each group is not very large and variations within groups is not is comparable for different groups.
Stratified Random Sampling. Google it. .
stratificatin
Cluster Sampling
It is called one-stage cluster sampling. If random samples are taken within the selected clusters then it is two-stage cluster sampling.
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.
You can't conduct startified sampling if there are no difinative groups, thus systematic sampling is more efficient if your data has no groups.
1. Simple Random Sampling (SRS) - For SRS, every element has an equal probability of being chosen. In fact, any pair, triplet, and so on of elements have an equal chance of random selection. Sometimes, SRS can have problems because the randomness of the sample does not represent the population. For example, a SRS of one hundred people will likely produce about fifty men and fifty women, but it's also possible that there will only be ten men and ninety women selected due to natural sampling variation. 2. Systematic Sampling - For this type of sampling, every nth element is sampled. For example, if names were to be sampled through systematic sampling, every tenth name would be picked from the telephone book. However, this type of sampling may result in an unrepresentative sample of the population. 3. Stratified Sampling - When a population has certain categories, samples can be purposely collected from each strata (category). For example, there may be different strata for age groups if the person sampling is interested in variations between differences in age. One problem with stratified sampling is that it requires a more expensive cost than simple random sampling or systematic sampling. 4. Convenience Sampling - This type of sampling involves drawing the easiest samples to reach from the population. This may include surveying customers outside of a grocery store. Because the sample is limited to a certain time/day, it is unrepresentative of the entire population.
In stratified sampling, the population to be sampled is divided into groups (strata), and then a simple random sample from each strata is selected. For example, a state could be separated into counties, a school could be separated into grades. These would be the 'strata'.
Stratified random sampling is a form of probability sampling that provides a methodology for dividing a population into smaller subgroups as a means of ensuring greater accuracy of your high-level survey results. The smaller subgroups are called strata. Stratified random sampling is also called proportional or quota random sampling.
both Macroevolution and Microevolution Good luck with Novanet. God help you.
both Macroevolution and Microevolution Good luck with Novanet. God help you.
both Macroevolution and Microevolution Good luck with Novanet. God help you.