Non-probability sampling methods

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HBS108 (Week 6 & 7) Mind Map on Non-probability sampling methods, created by shirley.ha on 02/09/2013.
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Mind Map by shirley.ha, updated more than 1 year ago
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Non-probability sampling methods
  1. used for practical reasons
    1. sually easier and cheaper to implement, but they may result in samples that are less representative of the whole population.
    2. Convenience
      1. involves selecting a sample from a convenient location without considering the degree to which the sample is representative.
        1. Clinical health research uses this
          1. taking the patients/participants who are available - as random sampling from the population is almost impossible
          2. Quota
            1. Under conveience
              1. and setting quotas for sub-groups prior to convenience sampling.
              2. Individuals who have certain characteristics of interest are selected from a convenient location until the required sample size is reached (the quota).
              3. Snowball
                1. using networks to identify a sample.
                  1. Used when sample frames not available
                  2. uses the first few participants with the desired characteristics to identify similar people to enlarge the group.
                    1. Ppl who meet criteria are selected
                      1. Collect the info
                        1. asked to identify other individuals who meet the sampling criteria
                  3. Purposive
                    1. researcher making a decision about who will be able to provide the desired information and only sampling from these identified individuals.
                      1. participants are handpicked as they have the information needed.
                        1. used when the population of interest is very small and it would not be practical or economical to sample the general population in order to identify them.
                        2. Is the sample rep of the whole pop?
                          1. Consider if adequate in size, is accurate in its characteristics and is complete.
                            1. consider the sampling method to be used.
                              1. Statisticians
                                1. use sampling distribution theory to help them to estimate how representative a sample is in relation to the target population
                                  1. Sampling error
                                    1. discrepancy between our sample mean and the true population mean (average).
                                      1. calculated from the sample size and the amount of variability in the sample.
                                        1. sample mean is rarely exactly equal to the population mean
                                          1. expect the sample mean to be close to the population mean (i.e. to estimate the population mean) provided we have used a robust sampling method.
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