Non Probability Sampling Methods Essay Example for Free

Non Probability take in Methods EssayNon- probability take is that sampling procedure which does not afford any basis for estimating the probability that severally item in the population has of being included in the sample. In this type of sampling, items for the sample be selected deliberately by the enquiryer his choice concerning the items remains supreme.Non-Probability consume MethodsThe common feature in non probability sampling methods is that subjective judgments ar utilise to determine the population that are contained in the sample. The common groups are discussed below1. Convenience try2. Judgement Sampling3. Quota Sampling4. Snowball samplingConvenience SamplingThis type of sampling is used primarily for reasons of convenience, researchers might either be in need of imperative data so cannot conduct a thorough research or it is simply to satisfy ones rareness ab reveal a subject. This form of sampling is used mostly in marketing studies. For example a new yog hurt processing company is interested in knowing opinions about the new return (issues like flavour of the yoghurt, consistency of the yoghurt and packaging). The perception is to produce what would best appeal to the customers. A nonpublic researcher has been hired and he asks his neighbours (convenient sample) their opinion about the yoghurt.Judgement SamplingThe researchers in-person judgement guides the selection criteria his discretion that the selected members are representative of the entire population guides the findings. It is used mainly in product tests.For example a research team has been constituted to conduct a survey, if one of the members drops out the dominion investigator has the right to appoint a replacement. This would be done at the discretion of the principle investigator.6.3.1.3 Quota SamplingThis is a very commonly used sampling method in marketing research studies. Here the sample is selected on the basis of certain basic parameters such as age, sex, income and occupation that describe the nature a population so as to make it representative of the population. The Investigators or field workers are instructed to choose a sample that conforms to these parameters. The field workers are assigned quotas of the number of units satisfying the required characteristics on which data should be collected. However, before collecting data on these units, the investigators are supposed to verify that the units confine these characteristics. Suppose we are conducting a survey to study the get behavior of a product and it is believed that the buying behavior is greatly influenced by the income level of the consumers.We assume that it is possible to divide our population into three income strata such as high-income group, middle-income group and low-income group. Further it is known that 20% of the population is in high income group, 35% in the middle-income group and 45% in the low-income group. Suppose it is decided to select a sample of si ze two hundred from the population. Therefore, samples of size 40, 70 and90 should come from high income, middle income and low income groups respectively. Now the various field workers are assigned quotas to select the sample from each group in such a way that a total sample of 200 is selected in the same proportion as mentioned above.6.3.1.4 Snowball Sampling The sampling in which the selection of additional respondents (after the first small group of respondents is selected) is based upon referrals from the initial set of respondents. It is used to sample low incidence or rare populations It is done for the efficiency of finding the additional, hard-to-find members of the sample.6.3.1.5 Advantages of Non-probability Sampling It is often cheaper to probability sampling. It is acceptable when the level of accuracy of the research results is not of utmost importance. Less research metre is required than probability samples. It often produces samples quite similar to the popula tion of interest when conducted properly.6.3.1.6 Disadvantages of Non-probability Sampling You cannot calculate Sampling error. Thus, the minimum required sample size cannot be calculated which suggests that you (researcher) may sample too a few(prenominal) or too many members of the population of interest. You do not know the degree to which the sample is representative of the population from which it was drawn. The research results cannot be projected (generalized) to the total population of interest with any degree of confidence.