MATH 225 Week 1 Assignment – Comparing Sampling Methods | Complete Questions & Correct Answers (Chamberlain College of Nursing)

MATH 225 Week 1 Assignment – Comparing Sampling Methods | Complete Questions & Correct Answers (Chamberlain College of Nursing) Questions and Answers Q1. What is the purpose of using sampling in research rather than surveying an entire population? A1. Sampling allows researchers to study a manageable group of participants rather than an entire population, which may be too large, expensive, or time-consuming to survey completely. A well-chosen sample provides reliable insights that represent the population while reducing cost and effort. Q2. Define simple random sampling and provide an example. A2. Simple random sampling is a method where every individual in the population has an equal chance of being selected. For example, assigning numbers to all students in a class and randomly drawing names from a hat ensures each student has the same probability of selection. Q3. What is stratified sampling, and why is it useful in nursing research? A3. Stratified sampling involves dividing a population into subgroups (strata) based on shared characteristics (e.g., age, gender, diagnosis) and then sampling from each subgroup. In nursing research, it ensures representation of all important groups, improving accuracy when comparing health outcomes across demographics. Q4. Explain systematic sampling with an example. A4. Systematic sampling selects every kth individual from a list after choosing a random starting point. For example, if a hospital has 1,000 patients and a researcher needs 100, they could select every 10th patient from a randomly chosen starting number. Q5. Describe cluster sampling and provide a nursing-related example. A5. Cluster sampling divides a population into clusters (groups), then randomly selects entire clusters for study. For example, instead of sampling individual patients from all hospitals in a city, a researcher might randomly select 3 hospitals (clusters) and include all patients from those hospitals. Q6. Compare the advantages and disadvantages of stratified and cluster sampling. A6. Stratified sampling improves accuracy by ensuring representation of subgroups but can be time-consuming and requires detailed population data. Cluster sampling is more convenient and cost-effective, especially for large populations, but may introduce bias if selected clusters are not truly representative. Q7. Which sampling method is best suited for a nationwide nursing survey, and why? A7. Cluster sampling is often best for nationwide surveys because it reduces cost and logistics by selecting groups (e.g., hospitals or regions) rather than individuals across the whole country. However, researchers may combine cluster with stratified sampling for better representation.