Mean of Purposive sampling,

Mean of Purposive sampling,

 Cluster sampling,

 Simple Random Quota sampling Voluntial 

sampling Voluntary Sampling 

Stratified sampling Captive 

 sampling Accidental 

sampling Systematic sampling

Purposive sampling: Also known as judgmental, selective or subjective sampling is a type of non-probability sampling technique. Non-probability sampling focuses on sampling techniques where the units that are investigated are based on the judgment of the researcher. There are a number of different goals.    Cluster sampling: is a sampling technique used when “natural” but relative heterogeneous groupings are evident in a statistical population. It is often used in marketing research. In this technique, the total population is divided into these groups (or Clusters) and a sample random sample of the groups is selected. The elements in each cluster are sampled, and then this is referred to as a “one-stage” cluster design.     Systematic sampling: is a statistical method involving the selection of elements from an ordered sampling frame. The most common form of systematic sampling is an equal-probability method. In this approach, progression through the list is treated circularly, with a return to the top once the end of the list is passed.     Accidental sampling: is a type of non- probability sampling that involves the sample being drawn from that part of the population that is close to hand. That is, sample populations selected because it is readily available and convenient, as researchers are drawing on relationships or networks to which they have easy access. The researcher using such a sample cannot scientifically make generalizations about the total population from this sample because it would not be representative enough. For example, if the interviewer was to conduct such a survey at a shopping center early in the Moring on a given day, the people that he/she could interview would be limited to those given there at that given time, which would not represent the views of other members of society in such an area, if the survey was to be conducted at different times of day and several times per week.   Captive sampling: it comparison of 2 behavioral sampling method to establish a time budget in a captive female cheetah (Acinonyx jubatus) Behavioral studies of wild animals kept in captivity useful information for conservation programs and animal welfare.   Stratified sampling: is a method of sampling from a population. In statistical survey, when subpopulations within an overall population vary, it is advantageous to sample each subpopulation (stratum) independently. Example: Assume that we need to estimate average number of votes for each candidate in an election. Assume that country has three (3) towns:  Town A has 1 million factory workers, Town B has 2 million office workers, and Town C has 3 million retirees. We can choose to get a random sample of size 60 over entire population but there is some chance that the random sample turns out to be not well balanced across these town and hence is biased causing a significant error in estimation. Instead if we choose to take a random sample of 10, 20 and 30 from Town A, B and C respectively then we can produce a smaller error in estimation for the same total size of sample.          Voluntial sampling: Voluntary Sampling is one of the main types of non-probability sampling method. A voluntary sampling is made up of people who self-select into the survey. Often, these folks have a strong interest in the main topic of the survey. Suppose, for example, that a news show asks viewers to participate sample. The sample is chose by the viewers, not by the survey administrator.    Quota sampling: is a method for selecting survey participants that is a non-probabilistic version of stratified sampling. In quota sampling, a population is first segmented into mutually exclusive sub-groups, just as in stratified sampling. Then judgment is used to select the subjects or units from each segment based on a specified proportion. Example: an interviewer may be told to sample 200 females and 300 males between the age of 45 and 60. This means that individuals can put a demand on who they want to sample (targeting) the second step makes the technique non- probability sample.    Simple Random: in statistics, a simple random sample is a subset of individuals (a sample) chosen from a larger set (a population). Each individual is chose randomly and entirely by chance, such that each individual has the same probability of being chosen at any stage during the sampling process, and each subset of k individuals has the same probability of being chosen for the sample as any other subset of K individual. A simple Random sample is an unbiased surveying technique.