Population and Sampling – GCSE Statistics Edexcel Revision

Appreciate the concept of a population in statistics as a complete set of items that share at least one property in common that is the subject of a statistical analysis.
Identify a sample as a subset of the population which is selected for investigation; the properties of the sample will be analysed and then inferred to the whole population.
Understand sampling as the process of selecting a sample which will represent the population as closely as possible.

Identify random sampling as a technique where each member of the population has an equal chance of being selected.
Understand stratified random sampling as a method where the population is divided into relevant and different subgroups or ‘strata’, and a random sample is taken from each stratum proportional to its size.
Recognise systematic sampling as a sampling method where items or people of interest are chosen at regular periodic intervals from the larger population.
Understand cluster sampling as a method where the larger population is divided into sections or clusters, and then clusters are randomly selected and all members within chosen clusters are sampled.
Acknowledge quota sampling as a non-random sampling technique, where the researcher selects a specific number of individuals or units from each segment of the population, based on their representation in the entire population.

Appreciate that sampling saves time and resources when the population size is large and it is impracticable to study the whole population.
Recognise the potential for sampling error, a statistical error that occurs when an analyst does not select a sample that represents the entire population of data, leading to biased results.
Understand that the size of the sample and the method of sampling can significantly affect the reliability and validity of the statistical analysis.

Note that a larger sample size can yield a more accurate representation of the population and reduce the impact of outliers.
Understand that there is often a trade-off between the resources needed to collect a larger sample and the increased precision it provides.
Acknowledge that the optimal sample size depends on the level of accuracy required, the size of the population, and the resources available for the study.