Sampling Methods

Samples are broadly classified into two groups – Non Probability Samples and Probability Samples. Non Probability Samples are further divided into four types namely Judgement, Chunk, Quota and Convenience. Probability Samples are further divided into four types – Simple random, Systematic, Stratified and Cluster sampling. Let us look into each type in detail. In non-probability sampling it is assumed that there is an even distribution of characteristics within the population. Hence, researcher believes that any sample is representative of the population and would fetch accurate results. However there is no such assumption in probability. Randomization is a feature of selection process.

Convenience sampling method includes formation of samples based on the convenient method (ease of access) as per the researcher. Sampling of employees, shoppers in a mall etc. are examples of convenience sampling. This type of sampling is a biased sampling as researcher may approach certain type of people any this may not represent the population. Judgemental sampling is based on expert opinion. In this type of sampling researcher may choose sample depending upon who they think are appropriate for study and may not find sample representing the population. Next type of sampling is quota sampling method. In this method we study the population and find out the proportional mix of the population and choose sample elements in the same proportion as the population. For example if the population consists of 60:40 male to female ratio then the sample is chosen in 60:40 ratio. Sample obtained through this method is perfect representation of the population. The drawback of the method is getting such details about the population. Fourth method in non-probability sampling technique is snowball sampling method. This method is based on referral. First respondent refers a friend and that friend refers his friend and the chain continues.

Let us have a look at probability sampling methods. First method is simple random sampling technique. In this method sample elements are chosen randomly from the population. Every item has an equal chance of being selected. Selection may be done with replacement or without replacement. Selection of sample of students from a group of students based on their roll number is an example of simple random sample. Second method is systematic sampling method. In this method population is divided into certain frames and k th element is chosen from each frame. Choosing every 4th student from a class of 80 students is an example of systematic sampling. Next is cluster sampling. In this method population is divided into different clusters which represent the population. These clusters are heterogeneous within and homogeneous external and represent the population. The last method is stratified sampling method. In this method population is divided depending upon certain common characteristics known as strata. A simple random sample is selected from each strata in proportional sizes and combined to form a sample known as stratified sample. This method ensures representation of individuals across the entire population. This method is extensively used by researchers for sampling.



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