Abstract:This article studied and compared the two nonprobability sampling techniques namely, Convenience

This article is on representation of basis and the basis selection of techniques. The representation of this two is performed either by the method of probability random sampling or by the method of non-probability random sampling. The selection of random type is done by probability random sampling while the non-selection type is by non-probability probability random sampling. This selection of techniques is talking about either without control (unrestricted) or with control (restricted) when individually the element of each sample is selected from a given totality, the drawn of sample element goes with unrestricted while all the other types of the sampling is to be considered as a restricted sampling. IntroductionThe aim of this article is to discuss about the sampling and sampling technicality. Statistical agencies prefer the probability random sampling. In business, companies, marketers mostly relay on non-probability sampling for their research, the researcher prefers that because of getting confidence cooperation from his respondent especially in the business sample survey like consumer price index. In New Zealand the proficient set on consumer price index committee advice the government on the their CPI. Non-Probability SamplingNon-probability sampling is a sampling procedure that will not bid a basis for any opinion of probability that elements in the universe will have a chance to be included in the study sample. We are going to see from diverse method of five different sampling considering the non-random designs. which are; Quota sampling, Accidental sampling, Judgemental sampling or Purposive sampling, Expert sampling, Snowball sampling, Modal instant sampling .From the listed the researcher has to deliberately select items to be sample. This type of sampling is costly in application. Types of Non-Probability Random Sampling Quota samplingThe researcher here is ease of access to his sample population by using quota sample, his tallying will be at his convenience guide by some evident of characteristic, such as sex, race, based on population of interest. The sample selection is by the convenient door of the researcher, Any person or individual mistakenly seen with the same characteristics will be asked pertaining the subject of the research for inclusion. It will flow in the same manner until the desired number is achieved. Quota sampling is of two types; first proportionate quota sampling represent the characteristics of major population by sampling a proportional total. Example if we are interested in studying population of 40 percent of females and 60 percent of males. We need a 100 size for the sample; the selection will not stop unless the target is hit before stopping. Meanwhile when the exact number of either male or female is gotten, say 40 female, the selection for the male has to continue in the same process, eventually when a legitimate female comes across, it will not be selected because there number is already completed.The major setback of purposive sampling is that you necessity to...

The article provides the description and comparison of two non-random samplings which are snowball or chain referral sampling and sequential sampling. Snowball sampling has been widely used in qualitative sociological research, especially in the study of deviant behavior and is used in the place where the population is hard to reach. It also described different form of sampling method. While in sequential sampling, sampling was taken at a given time interval and modification can be made by correcting the research and sampling method to centralize the analysis and make a satisfied decision.

This article realizes a well define combination of probability random sampling and non-probability sampling, determination of differences and similarities was observed with the methods that is more consuming of time, cost effective and energy requiring or needed during the sampling is observed. The two shows similarities between them, the design is to provide sample that will go alone to answer research questions under investigation and generalizability of issues to an external situation or population that is for external validity. In case of the difference, the probability sampling lead in to greater breadth in positions of information from larger population of units selected that will represent the group. Then the non-probability sampling lead with greater depth of information with careful selecting of cases from a small number of units.

The possibility that researchers should be able to obtain data from all cases is questionable. There is a need; therefore, this article provides a probability and non-probability sampling. In this paper we studied the differences and similarities of the two with approach that is more of fritter away time, cost sufficient with energy required throughout the sample observed. The pair shows the differences and similarities between them, different articles were reviewed to compare the two. Quota sampling and Stratified sampling are close to each other. Both require the division into groups of the target population. The main goal of both methods is to select a representative sample and facilitate sub-group research. There are major variations, however. Stratified sampling uses simple random sampling when the categories are generated; sampling of the quota uses sampling of availability. For stratified sampling, a sampling frame is necessary, but not needed for quota sampling. More specifically, stratified sampling is a method of probability sampling which enables the calculation of the sampling error. For quota samples, this is not possible. Quota sampling is therefore primarily used by market analysts rather than stratified sampling, as it is mostly cost-effective and easy to conduct and has the appealing equity of satisfying population reach. However, it disguises potentially significant bias.