cluster

Examples of cluster in the following topics:

• Three sampling methods (special topic)

  • Then we sample a fixed number of clusters and collect a simple random sample within each cluster.
  • This technique is similar to strati ed sampling in its process, except that there is no requirement in cluster sampling to sample from every cluster.
  • Also, unlike stratified sampling, cluster sampling is most helpful when there is a lot of case-to-case variability within a cluster but the clusters themselves don't look very different from one another.
  • However, cluster sampling seems like a very good idea.
  • In the bottom panel, cluster sampling was used, where data were binned into nine clusters, three of the clusters were randomly selected, and six cases were randomly sampled in each of these clusters.

• Lab 2: Sampling Experiment

  • The student will demonstrate the simple random, systematic, stratified, and cluster sampling techniques.
  • NOTE : The following section contains restaurants stratified by city into columns and grouped horizontally by entree cost (clusters).
  • Pick a cluster sample of restaurants from two cities.

• Optional Collaborative Classrom Exercise

  • Create a cluster sample by considering each state as a stratum (group).
  • By using simple random sampling, select states to be part of the cluster.
  • Then survey every U.S. congressman in the cluster.

• Random Sampling

  • Cluster sampling divides the population into groups, or clusters.
  • Some of these clusters are randomly selected.
  • Then, all the individuals in the chosen cluster are selected to be in the sample.
  • Categorize a random sample as a simple random sample, a stratified random sample, a cluster sample, or a systematic sample

• Introduction to Bivariate Data

  • Second, the points cluster along a straight line.
  • Although the points cluster along a line, they are not clustered quite as closely as they are for the scatter plot of spousal age.
  • Scatter plots that show linear relationships between variables can differ in several ways including the slope of the line about which they cluster and how tightly the points cluster about the line.

• Optional Collaborative Classrom Exercise

  • Where do your data appear to cluster?
  • How could you interpret the clustering?

• Summary

• Displaying Data

  • The graph can be a more effective way of presenting data than a mass of numbers because we can see where data clusters and where there are only a few data values.

• Sampling

  • To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters.
  • All the members from these clusters are in the cluster sample.
  • The departments are the clusters.
  • All members of the four departments with those numbers are the cluster sample.
  • Determine the type of sampling used (simple random, stratified, systematic, cluster, or convenience).

• Transforming data (special topic)

  • There are some standard transformations that are often applied when much of the data cluster near zero (relative to the larger values in the data set) and all observations are positive.
  • We can see a positive association between the variables and that many observations are clustered near zero.