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- A cluster is a group of similar or related objects that share some common characteristics1234.Examples of clusters include1234:
- Market segments based on customer preferences or behavior
- Social network communities based on shared interests or connections
- Search results based on relevance or similarity
- Medical images based on tissue types or diseases
- Image segments based on color or texture
- Anomalies based on deviation from normal patterns
- Immunization coverage based on geographic areas or population groups
- Waterfowl density based on habitat or season
- Health status based on disaster impact or risk factors
- Forest inventory based on tree species or size
- Observations based on continuous or binary variables
- Points based on visual closeness on a graph
- Clusters based on distance connectivity, mean vectors, or statistical distributions
Learn more:✕This summary was generated using AI based on multiple online sources. To view the original source information, use the "Learn more" links.Some common applications for clustering include the following:
- market segmentation
- social network analysis
- search result grouping
- medical imaging
developers.google.com/machine-learning/clusterin…Assess immunization coverage (Henderson & Sundaresan, 1982). Estimate density of waterfowl wintering (Smith, Conroy, & Brakhage, 1995). Conduct a rapid assessment of health in communities affected by natural disasters (Malilay, Flanders, & Brogan, 1996). Determine forest inventories (Roesch, 1993).
www.simplypsychology.org/cluster-sampling.htmlData clusters can be complex or simple. A complicated example is a multidimensional group of observations based on a number of continuous or binary variables, or a combination of both. A simple example is a two-dimensional group based on visual closeness between points on a graph.analystanswers.com/data-cluster-definition-exampl…Typical cluster models include:
- Connectivity models: for example, hierarchical clustering builds models based on distance connectivity.
en.wikipedia.org/wiki/Cluster_analysis - People also ask
Cluster Sampling: Definition, Advantages & Examples
For example, imagine we are studying rural communities in a state. Simple random sampling requires us to travel to all these communities just to get a few subjects from each place, which could be cost and time prohibitive. However, we can divide rural communities into similar groups. Then, we pick a random … See more
Cluster sampling is a method of obtaining a representative sample from a population that researchers have divided into groups. An individual cluster is a subgroup that mirrors the diversity of the whole population while the set of clusters are similar to each other. … See more
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After researchers identify their clusters, they need to decide which approach they’ll use, single-stage or two-stage sampling. See more
Both cluster and stratified sampling have the researchers divide the population into subgroups, and both are probability sampling methods that aim to obtain a representative sample. However, beyond those similarities, the goals and techniques are … See more
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