When a small group has taken as a representative of the whole, it’s called as sampling. It’s the small unit which make a good use in analysis of research finding.
Types of Sampling:
- Random Sampling
- Lottery Sampling
- Sequential Sampling
- Grid Sampling
- Biased Sampling
- Stratified Sampling
- Quota Sampling
- Multistage Sampling
- Convenience Sampling
- Self-selected Sampling
1. Random SamplingIt’s called as the proportional sampling. It assures each individual or elements in the universe has equal chance of being selected or choosed research unit. It’s a popular method in statistics to justify the method of research.
2. Lottery Sampling
Some time it’s impossible to cover all the area, so the researcher may do the lottery system to select a particular area for her/his research designing.
3. Sequential samplingThe scholar collects the sequential list to select her/his samples. In a sequence if a number is more samples are drawn from that sequence. Usually alphabetical order dominate in sequential sampling.
4. Grid samplingGrid sampling refers to election of a particular area from the total Universe. In such a method of sampling the entire universe is divided into different greed and segments and the scholar prepares a map of the entire universe and places the greed in that map out of which he selects her/his samples for study & research.
5. Biased samplingBiased sampling means a researcher selects the samples according to her/his choice and is free to choose one & reject the other.
6. Stratified samplingIt includes both perpessive and random sampling. Strata implies groups. The entire universe is divided into different groups or strata and samples are done from each group or strata.
7. Quota samplingQuota sampling is a type of perpessive sampling, the entire universe is divided into different groups, strata or physical regions and from each group, strata or region we draws specific samples according to our quota that means, selection must be according to the need of the area.
8. Multi-stage samplingThe universe is always very large and there must be a proper parameter to select samples, which adequately represents the universe. For that purpose we divide the total universe into different stages and accordingly we select samples.
9. Convenience samplingWhere the universe isn’t very clear to understand for research, the researcher use this type off sampling.
10. Self-selected sampling
Selection is done by the people. In such cases the researcher needn’t go to the respondents, rather the respondent run after the researcher for selection.
4. Grid samplingGrid sampling refers to election of a particular area from the total Universe. In such a method of sampling the entire universe is divided into different greed and segments and the scholar prepares a map of the entire universe and places the greed in that map out of which he selects her/his samples for study & research.
5. Biased samplingBiased sampling means a researcher selects the samples according to her/his choice and is free to choose one & reject the other.
6. Stratified samplingIt includes both perpessive and random sampling. Strata implies groups. The entire universe is divided into different groups or strata and samples are done from each group or strata.
7. Quota samplingQuota sampling is a type of perpessive sampling, the entire universe is divided into different groups, strata or physical regions and from each group, strata or region we draws specific samples according to our quota that means, selection must be according to the need of the area.
8. Multi-stage samplingThe universe is always very large and there must be a proper parameter to select samples, which adequately represents the universe. For that purpose we divide the total universe into different stages and accordingly we select samples.
9. Convenience samplingWhere the universe isn’t very clear to understand for research, the researcher use this type off sampling.
10. Self-selected sampling
Selection is done by the people. In such cases the researcher needn’t go to the respondents, rather the respondent run after the researcher for selection.
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