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 simila
Example: A worker wants to determine the average weight of fish fillets in its freezer. There are hundreds of boxes of fillets in the freezer.(1) He defines each box of fish as a cluster (hence there are hundreds of clusters)(2) He randomly selects 10 boxes of fish (cluste...
Example: Multistage samplingInstead of collecting data from every seventh-grader in the selected schools, you narrow down your sample in two additional stages: From each school, you randomly select a sample of seventh-grade classes. From within those classes, you randomly select a sample of studen...
Example of Two-Stage Cluster Sampling A garment manufacturer has N = 90 plants located throughout the United States and wants to estimate the average number of hours that the sewing machines were down for repairs in the past months. Because the plants are widely scattered, she decides to ...
The quality of statistical inference is dependent not only on, for example, estimator construction but on the structure of a population and a sampling scheme too. For example, let the estimation of total wheat production in a population of farms be considered. The population of farms is divided...
Cluster sampling is a probability sampling technique where researchers divide the population into multiple groups (clusters) for research. So, researchers then select random groups with a simple random or systematic random sampling technique for data collection and unit of analysis. Example: A researcher...
The cluster method must not be confused with stratified sampling. In stratified sampling, the population is divided into mutually exclusive groups that are externally heterogeneous but internally homogeneous. For example, in stratified sampling, a researcher may divide the population into two groups: mal...
The important thing to remember about this sampling technique is to give all the clusters equal chances of being selected. Types of Cluster Sample One-Stage Cluster Sample Recall the example given above; one-stage cluster sample occurs when the researcher includes all the high school students from...
give an example. Why is effective sampling important when performing a hypothesis test? What could happen if your sample is not appropriate to your study? Explain why increasing the sample size decreases the variability Explain how frequency is used to inform probability and why this...
This method combines the sampling technique with PAM; however, it is not limited to a single sample at a specific time. CLARANS represents a sample with some randomness in each phase of the search, whereas CLARA has a fixed sample at every step of the search. The clustering approach can ...