There are many many ways. One method is called mark-recapture. The simplest method involves taking 2 samples. In the first sample, all the animals that are captured are marked (this can be leg bands, ear tags, toe clipping, or even using photoID in the case of whales/tigers). The size of this sample is called M to denoted that this is now our population of Marked animals. The second sample, which is collected at a later date, will usually (hopefully) contain some of the previously marked animals, and some animals that weren't previously caught. The size of the second sample is denoted n, and the number of marked animals in it is called m.
But we want to know N - the total population size. We can assume that the ratio of marked animals in our second sample (m/n) is the same as the ratio of marked animals in the population (M/N).
Therefore:
M/N=m/n
Rearrange it:
N=(n*M)/m
We know the values for M,n, and m so we can figure out N.
This is the simplest case, and is know as the Lincoln-Peterson estimator. There are many extensions to this that allow for more samples etc.
Stratified sampling
Sampling error occurs when the sampling protocol does not produce a representative sample. It may be that the sampling technique over represented a certain portion of the population, causing sample bias in the final study population.
This technique is used when natural but relatively homogenous groupings are evident in a statistical population. This technique is commonly used in marketing research. The technique splits the population into groups and only a simple random group is selected.
Quota sampling.
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.
Stratified sampling
Clustered sampling.Clustered sampling.Clustered sampling.Clustered sampling.
it's a random sampling technique formula to estimate sampling size n=N/1+N(e)2 n- sampling size N-total population e-level of confidence
Disadvantages of systematic sampling: © The process of selection can interact with a hidden periodic trait within the population. If the sampling technique coincides with the periodicity of the trait, the sampling technique will no longer be random and representativeness of the sample is compromised.
Sampling error occurs when the sampling protocol does not produce a representative sample. It may be that the sampling technique over represented a certain portion of the population, causing sample bias in the final study population.
Random Sampling is the most common sampling technique
Sampling is needed in order to determine the properties of a distribution or a population. Sampling allows the scientist to determine the variance in an estimate.
In many cases, it is not even possible to count signs of every member of a population. The population may be very large or spread over a wide area. In such cases ecologists usually make an estimate. An estimate is an approximation of number, based on reasonable assumptions.
stratified sampling technique
it's a random sampling technique formula to estimate sampling sizen=N/1+N(e)2n- sampling sizeN-total populatione-level of confidence
This technique is used when natural but relatively homogenous groupings are evident in a statistical population. This technique is commonly used in marketing research. The technique splits the population into groups and only a simple random group is selected.
Quota sampling.