Key concepts

 A correlational study is a scientific study in which a researcher investigates associations between variables.

Cluster sampling is a sampling technique used when "natural" but relatively homogeneous groupings are evident in a statistical population. It is often used in marketing research.

Cluster sampling refers to a sampling method that has the following properties.

• The population is divided into N groups, called clusters.
• The researcher randomly selects n clusters to include in the sample.
• The number of observations within each cluster M_i is known, and M = M₁ + M₂ + M₃ + ... + M_N-1 + M_N.
• Each element of the population can be assigned to one, and only one, cluster.

This tutorial covers two types of cluster sampling methods.

• One-stage sampling. All of the elements within selected clusters are included in the sample.
• Two-stage sampling. A subset of elements within selected clusters are randomly selected for inclusion in the sample.

Survey method in which groups (clusters) of sampling units (and not individual units) are selected from a population for analysis. In cluster sampling, instead of selecting all the subjects from the entire population right off, the researcher takes several steps in gathering his sample population.

In cluster sampling, instead of selecting all the subjects from the entire population right off, the researcher takes several steps in gathering his sample population.

Advantages: saves time, less expensive, can show "regional variation"

Cluster sampling is a sampling technique used when "natural" but relatively homogeneous groupings are evident in a statistical population. It is often used in marketing research. In this technique, the total population is divided into these groups (or clusters) and a simple random sample of the groups is selected. Then the required information is collected from a simple random sample of the elements within each selected group. This may be done for every element in these groups or a subsample of elements may be selected within each of these groups. A common motivation for cluster sampling is to reduce the total number of interviews and costs given the desired accuracy. Assuming a fixed sample size, the technique gives more accurate results when most of the variation in the population is within the groups, not between them.

Cluster sampling refers to a sampling method that has the following properties.

• The population is divided into N groups, called clusters.
• The researcher randomly selects n clusters to include in the sample.
• The number of observations within each cluster M_i is known, and M = M₁ + M₂ + M₃ + ... + M_N-1 + M_N.
• Each element of the population can be assigned to one, and only one, cluster.

1. Cluster sampling is a sampling technique used when "natural" but relatively homogeneous groupings are evident in a statistical population. It is often used in marketing research.

Cluster sampling is a sampling technique used when "natural" but relatively homogeneous groupings are evident in a statistical population. It is often used in marketing research. In this technique, the total population is divided into these groups (or clusters) and a simple random sample of the groups is selected. Then the required information is collected from a simple random sample of the elements within each selected group. This may be done for every element in these groups or a subsample of elements may be selected within each of these groups

Survey method in which groups (clusters) of sampling units (and not individual units) are selected from a population for analysis.

Cluster sampling refers to a type of sampling method . With cluster sampling, the researcher divides the population into separate groups, called clusters. Then, a simple random sample of clusters is selected from the population. The researcher conducts his analysis on data from the sampled clusters.