Question

Post a description of the types of probability and nonprobability sampling you selected. Then describe two strengths and two weaknesses of each type of sampling. Finally, identify two ethical considerations that may factor into selecting a sampling method and explain how you might address these considerations.

Answer 1

Probability Sampling:

What is Probability Sampling?

• Probability sampling: In this Sampling  every unit in the population/Set has a equal chance (greater than zero) of being selected in the sample, and this probability can be accurately determined

• Non-probability sampling: In this Sampling  every unit in the population/Set has a Unequal chance (greater than zero) of being selected in the sample, and this probability can be accurately determined.Here some units may have Zero probability of being selected at all.

Types of Probability Sampling

1. Simple random sampling: In a simple random sample of a given size, all elements of the Set are given an equal probability. Each element of the Set thus has an equal probability of selection.The Set  is not subdivided or partitioned.
2. Stratified Random Sampling When the population embraces a number of distinct categories, the frame can be organized by these categories into separate "strata." Each stratum is then sampled as an independent sub-population, out of which individual elements can be randomly selected
3. Systematic Sampling Systematic sampling (also known as interval sampling) relies on arranging the study population according to some ordering scheme and then selecting elements at regular intervals through that ordered list.Systematic sampling involves a random start and then proceeds with the selection of every kth element from then onwards

• Cluster Random Sampling is a way to randomly select participants from a list that is too large for simple random sampling. For example, if you wanted to choose 1000 participants from the entire population of the U.S., it is likely impossible to get a complete list of everyone. Instead, the researcher randomly selects areas (i.e. cities or counties) and randomly selects from within those boundaries.
• Multi-Stage Random sampling uses a combination of techniques.

Advantages and Disadvantages

Each probability sampling method has its own unique advantages and disadvantages.

Advantages

• Cluster sampling: convenience and ease of use.
• Simple random sampling: creates samples that are highly representative of the population.
• Stratified random sampling: creates strata or layers that are highly representative of strata or layers in the population.
• Systematic sampling: creates samples that are highly representative of the population, without the need for a random number generator.

Disadvantages

• Cluster sampling: might not work well if unit members are not homogeneous (i.e. if they are different from each other).
• Simple random sampling: tedious and time consuming, especially when creating larger samples.
• Stratified random sampling: tedious and time consuming, especially when creating larger samples.
• Systematic sampling: not as random as simple random sampling,