Types of sampling design
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There are two main types of sampling design: probability/random sampling and non-random sampling. Probability sampling involves each member of the population having a known chance of being selected, such as simple random sampling using a lottery method or random number table. Non-random sampling involves selection based on the investigator's personal judgment, without all members having an equal chance, like convenience sampling. The sampling method depends on factors like the nature of the population, cost, and desired accuracy.
Types of sampling design
- 2. INTRODUCTION Sampling is considered with the selection of a subset of individual from within a statistical population to estimate the characteristics of the whole population. Sampling design or a working plan that specifies the population frame , sample size , sample selection and estimation method in detail. A variety of sampling techniques are available . The one selected depends upon the nature and relevance of the study and the information to be dealt with . Rather the purpose of the study determines the sampling to be adopted and finally the fund available. The various methods of sample can be broadly categorized into two as probability and non probability sampling . A brief discussion about this is done here.
- 3. PROBABILITY / RANDOM SAMPLING In probability sampling each member of the universe has a known chance of being selected for the sample . The main probability sampling methods are the following : Simple Random Sampling : Here each element of the frame have an equal probability of being selected. It is of two types : Lottery Method : The elements or the items of the universe numbered or written on separate slips and then it is drawn till we get the required sample size. Random Number Table : Here each member of the population is assigned a number and from some random point of the table of random numbers the random numbers are read out and items are selected till we get enough needed sample size.
- 4. Restricted Random Sampling : The selection of sample is based on subjective constraints to add more representativeness and meaning to the sample selected. It includes the following : Stratified random sampling : The population is divided into different segments called strata and each stratum in a strata are homogeneous in nature . The samples are selected either by proportionate method or by non - proportional method. Systematic Sampling / Quasi Random Sampling It is done when a complete list of population is available . Here a sampling interval is fixed by dividing the size of the universe . Cluster Sampling The population is subdivided into sampling units that are subdivided into units until an ideal level . The sample is selected from the lowest level.
- 5. Non Random Sampling / Non Probability Sampling In this method the probability of selection cant be accurately determined as the selection is based on the personal consideration of the investigator. Here some elements have no chance of selection. Some of the most popular non- probability sampling designs are : Sampling / Deliberate sampling : Selection of items for the sample is based on the personal judgment of the investigator after collecting necessary information . Quota Sampling : The population under study is divided into sub units called quota , based on common features . Then desired size of items are selected from each quota to form the sample space. Division and selection is based on personal judgment of the investigator. Convenience Sampling / Chunk Sampling : Here samples are obtained by selecting such units from the population which may be conveniently located and contacted.
- 6. CONCLUSION Within any of the type of frame identified before a variety of sampling methods can be employed individually or in combination. Factors commonly influencing the choice between these designs includes : Nature and quality of the frame. Availability of auxiliary information about units on the frame. Accuracy requirements and the need to measure accuracy. Whether detailed analysis of the sample is expected. Cost for operational concern
- 7. BIBLIOGRAPHY Vineeth K.M and M.C Deleep Kumar , Research Methodology , Kalyani Publishers (2010) Potti L.R , Fundamentals Of Business Statistics , Yamuna Publications http://en.wikipedia.org/statitical _sampling http://www.epa.gov/QUALITY/qksampl.html ****************
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