1.15
Cluster sampling is a widely used sampling method for marketing research where the population is large and geographically dispersed.
For example, researchers want to know the career choice of high school students in a city. This would involve surveying students from every school in the city, which is a time-consuming and expensive process. Even a randomly selected sample would not be an adequate representation of this large and diverse population.
Using cluster sampling, researchers divide the schools into different clusters and then randomly select some of the clusters to form the sample. Now, every student from those selected clusters is interviewed.
Thus, the researchers narrowed down the large population into several smaller clusters and randomly selected some of the clusters for the experiment.
Unlike cluster sampling, in stratified sampling, only a few individuals from each stratum are chosen. Also, in stratified sampling, each stratum is a homogeneous group, while in cluster sampling, the clusters are heterogeneous groups of individuals.
Although this method is easier and cost-effective, samples drawn from cluster sampling are more prone to bias and high sampling error.
Gepaste steekproefmethodes zorgen ervoor dat steekproeven zonder vertekening worden getrokken en de populatie nauwkeurig vertegenwoordigen. Omdat het meten van de gehele populatie in een onderzoek niet praktisch is, gebruiken onderzoekers steekproeven om de populatie van belang te vertegenwoordigen.
Om een clustersteekproef te kiezen, verdeel je de populatie in clusters (groepen) en selecteer je vervolgens willekeurig enkele van deze clusters. Alle leden van deze clusters maken deel uit van de clustersteekproef. Bijvoorbeeld, als je willekeurig vier afdelingen uit de populatie van een universiteit selecteert, vormen de vier afdelingen de clustersteekproef. Verdeel de faculteit van je hogeschool per afdeling. De afdelingen zijn de clusters. Nummer elke afdeling en kies vervolgens vier verschillende nummers met behulp van eenvoudige willekeurige steekproeftrekking. Alle leden van de vier afdelingen met die nummers vormen de clustersteekproef.
De clustersteekproef methode is kosteneffectief en bespaart tijd. Bijvoorbeeld, om de plattelandsgemeenschappen te bestuderen, wordt de staat verdeeld in clusters. In plaats van alle locaties te bezoeken, wordt een willekeurig cluster gekozen en bestudeerd, waardoor zowel geld als tijd wordt bespaard. Echter, clustersteekproeven bevatten meer steekproeffouten, omdat ze mogelijk niet de gehele populatie vertegenwoordigen.
Deze tekst is aangepast van Openstax, Introductory Statistics, Section 1.2 Data, Sampling, and Variation in Data and Sampling.
Cluster sampling is a widely used sampling method for marketing research where the population is large and geographically dispersed.
For example, researchers want to know the career choice of high school students in a city. This would involve surveying students from every school in the city, which is a time-consuming and expensive process. Even a randomly selected sample would not be an adequate representation of this large and diverse population.
Using cluster sampling, researchers divide the schools into different clusters and then randomly select some of the clusters to form the sample. Now, every student from those selected clusters is interviewed.
Thus, the researchers narrowed down the large population into several smaller clusters and randomly selected some of the clusters for the experiment.
Unlike cluster sampling, in stratified sampling, only a few individuals from each stratum are chosen. Also, in stratified sampling, each stratum is a homogeneous group, while in cluster sampling, the clusters are heterogeneous groups of individuals.
Although this method is easier and cost-effective, samples drawn from cluster sampling are more prone to bias and high sampling error.
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