Non Probability Sampling Methods Essay Example for Free

Non Probability Sampling Methods Essay Non-probability sampling is that sampling procedure which does not afford any basis for estimating the probability that each item in the population has of being included in the sample. In this type of sampling, items for the sample are selected deliberately by the researcher; his choice concerning the items remains supreme. Non-Probability Sampling Methods: The common feature in non probability sampling methods is that subjective judgments are used to determine the population that are contained in the sample. The common groups are discussed below; 1. Convenience Sampling 2. Judgement Sampling 3. Quota Sampling 4. Snowball sampling Convenience Sampling This type of sampling is used primarily for reasons of convenience, researchers might either be in need of urgent data so cannot conduct a thorough research or it is simply to satisfy ones curiosity about a subject. This form of sampling is used mostly in marketing studies. For example; a new yoghurt processing company is interested in knowing opinions about the new product (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 private researcher has been hired and he asks his neighbours (convenient sample) their opinion about the yoghurt. Judgement Sampling The researcher’s personal 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 principle investigator has the right to appoint a replacement. This would be done at the discretion of the principle investigator. 6.3.1.3 Quota Sampling This 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 qualify these characteristics. Suppose we are conducting a survey to study the buying 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 size 200 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 much cheaper to probability sampling.  · It is acceptable when the level of accuracy of the research results is not of utmost importance.  · Less research time is required than probability samples.  · It often produces samples quite similar to the population 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 few 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.