You are conducting a survey for a national organization with 25,689 dues-paying members. (a) What sampling method would be the most logical to use? (b) What are the steps you would use to develop the sample? (c) What are the advantages AND disadvantages of this type of sampling method?
(a) The most logical sampling method to use in this scenario would be stratified sampling.
(b) Steps to develop the sample using stratified sampling:
1. Define the population: In this case, the population would be the 25,689 dues-paying members of the national organization.
2. Identify relevant stratification factors: Stratification involves dividing the population into distinct groups or strata based on certain characteristics that are relevant to the research objectives. For example, these stratification factors could include age, gender, geographical location, or membership tenure.
3. Determine the sample size: Decide on the desired sample size for each stratum. To ensure the sample is representative, the sample size for each stratum should be proportional to the size of that stratum within the population.
4. Randomly select participants within each stratum: Use a random sampling technique, such as simple random sampling or systematic sampling, to select the desired number of participants from each stratum. This ensures that every member within each stratum has an equal chance of being selected.
5. Combine the samples: Combine the selected participants from each stratum to form the final sample.
(c) Advantages and disadvantages of stratified sampling:
Advantages:
1. Improved representation: Stratified sampling ensures that each subgroup within the population is adequately represented in the sample, leading to more accurate and reliable results.
2. Precision: By selecting larger sample sizes in larger strata and smaller sample sizes in smaller strata, stratified sampling allows for precise estimation of the population parameters for each subgroup.
3. Comparisons: Stratification allows for meaningful comparisons between different subgroups within the population.
Disadvantages:
1. Complexity: Implementing stratified sampling can be more complex compared to other sampling methods, as it requires the identification of relevant stratification factors and appropriate sample sizes for each stratum.
2. Cost and time: Stratified sampling may be more time-consuming and costly due to the need to select and collect data from multiple strata.
3. Potential bias: If the stratification factors are not carefully chosen or do not fully represent the population characteristics, the sample may still introduce biases.
Overall, stratified sampling provides better representation of different subgroups within the population and allows for more precise estimation, but it requires careful planning and consideration of relevant stratification factors.