What is Population, Sample and Sampling Error?
Population
A population is an entire dataset that we wish to draw the conclusion of. Denoted by “N”. A parameter is a measure that describes the whole population.
Sample
A subset of the population is a sample. Denoted by “n”. In general, it is impractical to collect data for the entire population so we have to rely on sample, which are small, manageable, cost effective and representative of the whole population. A statistic is a measure that describes the sample.
Sampling Error
Sampling Error is the difference between the population parameter and sample statistics. Sampling error can occur due to random selection of sample (as the sample is not representing the entire population in a better way). In general the aim is to generalize the findings from sample to entire population, hence we need sampling error to be low. One way of doing that is increasing a sample size. Other could be selecting sample in such a way that it will represent the population
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