# Types of sampling techniques broadly can be

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Types of Sampling Techniques: Broadly can be classified as a) Probability Sampling b) Non-probability Sampling 8.3.4. PROBABILITY SAMPLING Probability sampling provides a scientific technique of drawing samples from population according to some laws, of chance in which each unit has some definite pre-assigned probability of being chosen in sample. Random Sampling, Systematic Sampling, Stratified Sampling, Cluster Sampling, Multi-Stage Sampling and Area Sampling are considered under this category. 8.3.5. NON-PROBABILITY SAMPLING It is purely based on personal judgment. Under this method a desired number of sample units are selected deliberately or purposely depending upon object of the enquiry so that only the important items representing the true characteristics of population are included. Purpose Sampling, Quota Sampling and convenience sampling are considered as non-probability sampling.

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67 Probability Sampling Random Sampling: A random sampling is a sample selected in such a way that every item in the population has an equal chance of being included. It’s more suitable for homogeneous and comparatively large groups. Selection of Random Sampling: 1. Lottery Method 2. Use of Table of Random Number 3. Selecting from Sequential List 4. Grid System Merits of Random Sampling: 1. It is scientific and eliminates personal bias. 2. No advance knowledge of characteristics of population is required. 3. Assessment of accuracy of result is possible with sample error estimation. 4. It is true representation of universe 5. It is simple and practicable. 6. It provides reliable and maximum information saving money, time and labour. Demerits: 1. It requires the complete list of universe but such upto date may not be available. 2. In field survey, samples may be scattered widely, then is time consuming. 3. If it is small, representation may not be true. 4. For given degree of accuracy, size of sample is being increased. Stratified Random Sampling: In this population is divided into groups (Strata) according to geographical, sociological or economic characteristics. To obtain more efficient and accurate results when population is heterogeneous in variables under study. Process of Stratifying: 1. Population is divided into sub groups and required units are selected at random from each group. 2. Should be selected in such a way that item in one stratum should be similar to each other and differ significantly from other unit of other strata. 3. Strata must not overlap in variables 4. Strata must be large enough to provide selection of items. 5. Size of the sample from each stratum can be proportional or disproportional to the size of stratum.
68 Merits: 1. Correct stratification, even if it is small will represent the sample. 2. No significant group is left unrepresented.

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• Spring '12
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