Random/Representative Sampling

Random/representative sampling

1.Describe the issue/concept


Random sample: chosen through a method of unpredictable components. Therefore the estimates from random samples can be quite uncertain. In random sampling, each element of the population has an equal chance of being chosen at each draw. So it is not unfair or biased.

Representative sample: Where individuals are selected as a representation of the larger population. In statistical sampling, people gather data from a small group and try to make generalisations about a larger group.

2.What implication(s) does this have for knowledge gained in the human sciences (how does this issue or concept affect our ability to learn and know things via the human sciences)

Random sample: The positive aspects of having a random sample is that the results are not biased or unfair in any way. The samples are selected by random are so are not affected by personal opinion. The problems that could arise from this random selection, would be that it is left to chance. As each sample is equally likely to be chosen, they all have an equal chance. As humans are all different, there are no two humans that are the same, it is quite to determine whether those that are selected randomly, are a good sample for what is to be looked for. For example, if we were to study whether all people would flinch when being hit, and we used a random selection of people. The results would be determined by whether that sample of people had flinched or not. Thus if we had managed to select a group of people that all flinched we would conclude that people always flinched when being hit. But, we can not be certain as what if people that did not flinch had just not been selected.

Representative sample: The benefits of representative sampling is that it is more time and cost efficient, as only a smaller sample is needed to collect data from. This sample can then be used as a representation of the larger population, without having to collect data from all the individuals in the larger population. This is extremely beneficial for the human sciences as there are just so many humans in the world. It is almost impossible to get results from every last person on earth. Therefore it is much easier to sample a smaller group and use this as a representation of the larger group. The problems with this is then the fact that each individual is different and how can you assume that if something that applies to the smaller sample will apply to the larger population.

Random/representative sampling: The main benefit of simple random sampling is that it can guarantee that the sample chosen is representative of the population. As the sample was chosen at random out of that larger population. Therefore the statistical conclusions will be valid.