In probability sampling, it is possible to both determine which sampling units belong to which sample and the probability that each sample will be selected. The following sampling methods are examples of probability sampling: Show
Of the five methods listed above, students have the most trouble distinguishing between stratified sampling and cluster sampling. Stratified Sampling is possible when it makes sense to partition the population into groups based on a factor that may influence the variable that is being measured. These groups are then called strata. An individual group is called a stratum. With stratified sampling one should:
Stratified sampling works best when a heterogeneous population is split into fairly homogeneous groups. Under these conditions, stratification generally produces more precise estimates of the population percents than estimates that would be found from a simple random sample. Table 2.2 shows some examples of ways to obtain a stratified sample. Table 2.2. Examples of Stratified Samples
Cluster Sampling is very different from Stratified Sampling. With cluster sampling, one should
It is important to note that, unlike with the strata in stratified sampling, the clusters should be microcosms, rather than subsections, of the population. Each cluster should be heterogeneous. Additionally, the statistical analysis used with cluster sampling is not only different but also more complicated than that used with stratified sampling. Table 2.3. Examples of Cluster Samples
Each of the three examples that are found in Tables 2.2 and 2.3 was used to illustrate how both stratified and cluster sampling could be accomplished. However, there are obviously times when one sampling method is preferred over the other. The following explanations add some clarification about when to use which method.
The most common method of carrying out a poll today is using Random Digit Dialing in which a machine random dials phone numbers. Some polls go even farther and have a machine conduct the interview itself rather than just dialing the number! Such "robocall polls" can be very biased because they have extremely low response rates (most people don't like speaking to a machine) and because federal law prevents such calls to cell phones. Since the people who have landline phone service tend to be older than people who have cell phone service only, another potential source of bias is introduced. National polling organizations that use random digit dialing in conducting interviewer based polls are very careful to match the number of landline versus cell phones to the population they are trying to survey. Which of the following is a sampling method in which the whole population is subdivided into clusters or groups and random samples?Cluster random sample: The population is first split into groups. The overall sample consists of every member from some of the groups. The groups are selected at random.
Which of the following is a sampling method in which the population is first divided into?A sample may be selected from a population through a number of ways, one of which is the stratified random sampling method. Stratified random sampling involves dividing the entire population into homogeneous groups called strata (plural for stratum). Random samples are then selected from each stratum.
Which of the following is sampling method in which every element of the population has the same probability of being selected for inclusion in the sample?Simple random sampling. In simple random sampling (SRS), each sampling unit of a population has an equal chance of being included in the sample. Consequently, each possible sample also has an equal chance of being selected.
Is a sampling method used when the population is subdivided into clusters?Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.
|