Tuesday, 8 October 2013

Group 7 - Probability & Non - Sampling in Sampling (Pranitaa Shetty 2013042)

DEFINITION OF SAMPLE
The sample method involves taking a representative selection of the population and using the data collected as research information. A sample is a “subgroup of a population”. It has also been described as a representative “taste” of a group The sample should be “representative in the sense that each sampled unit will represent the characteristics of a known number of units in the population” The standard definition always includes the ability of the research to select a portion of the population that is truly representative of said population.

PROBABILITY SAMPLING
Probability sampling is sometimes called random sampling. Probability sampling provides an advantage because of researcher’s ability to calculate specific bias and error in regards to the data collected. Probability sampling is defined as having the “distinguishing characteristic that each unit in the population has a known, nonzero probability of being included in the sample”. It is described more clearly as “every subject or unit has an equal chance of being selected” from the population. It is important to give everyone an equal chance of being selected because it “eliminates the danger of researchers biasing the selection process because of their own opinions or desires”.When bias is eliminated, the results of the research may be generalized from the sample to the whole of the population because “the sample represents the population”
TYPES OF PROBABILITY SAMPLING
Simple: Each member of the study population has an equal probability of being selected.
Systematic: Each member of the study population is either assembled or listed, a random start is designated,  then members of the population are selected at equal intervals
Stratified: Each member of the study population is assigned to a group or stratum, then a simple random sample is selected from each stratum.
Cluster: Each member of the study population is assigned to a group or cluster, then clusters are selected at random and all members of a selected cluster are included in the sample.

NON-PROBABILITY SAMPLING
Non-probability sampling is sometimes called non-random sampling. Non-probability sampling is a good method to use when conducting a pilot study, when attempting to question groups who may have sensitivities to the questions being asked and may not want answer those questions honestly, and for those situations when ethical concerns may keep the researcher from speaking to every member of a specific group. Non-probability sampling is a good method to use when conducting a pilot study, when attempting to question groups who may have sensitivities to the questions being asked and may not want answer those questions honestly, and for those situations when ethical concerns may keep the researcher from speaking to every member of a specific group.




NON-PROBABILITY SAMPLING METHODS
         Convenience: Select cases based on their availability for the study.
   Purposive: Select cases that judged to represent similar characteristics.
   Snowball: Group members identify additional members to be included in the sample.
   Quota: Interviewers select a sample that yields the same proportions as the  population   proportions on easily identified variable


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