I don't under stand can some help me??
A.
List 2 examples of when you would use one of the various sampling techniques in the health care profession?
B.
When might you use one sampling technique over another?
C.
State the drawbacks of each sampling method.
Please go back and check your text about sampling techniques.
If you post these sampling techniques, we'll be glad to help you apply them to these questions.
EXAMPLE 3 Telephone Book Sampling
You want to conduct an opinion poll in which the population is all the residents in a town.
Could you choose a simple random sample by randomly selecting names from the local telephone
book?
Solution A sample drawn from a telephone book is not a simple random sample of the
town population because phone books invariably are missing a lot of names, and anyone whose
name is missing has no chance of being selected. For example, the phone book will be missing
names when two or more people share the same phone number but have only one listing, when
people choose to have an unlisted phone number or to rely exclusively on a cell phone, or when
people (such as the homeless) don’t have a telephone.
Systematic Sampling
Simple random sampling is effective, but in many cases we can get equally good results with a
simpler technique. Suppose you are testing the quality of microchips produced by Intel. As the
chips roll off the assembly line, you might decide to test every 50th chip. This ought to give a
representative sample because there’s no reason to believe that every 50th chip has any special
characteristics compared to other chips. This type of sampling, in which we use a system such
as choosing every 50th member of a population, is called systematic sampling.
For example, if I wanted to find out whether or not college students have health insurance, I would take a convenience sample using the students in this course since the students in this class are easily accessible and that is a characteristic of the convenience sampling technique. A drawback of this sampling technique is that a convenience sample is not normally a good sample that represents the population of the students that attend University of Phoenix. This class may have 25 students and the population of the University may be 15,000 students or more. The data in a convenience sample is likely to be skewed.
The type of sampling you might use in the health professions would vary depending on the hypothesis you are testing and your intended population. What are they?
I hope this helps a little. Thanksfor asking.
google your questions and u might get help.
Of course, I'll be happy to help you understand. Let's break down each question and explain how to find the answers:
A. To list 2 examples of when you would use one of the various sampling techniques in the health care profession, you can start by understanding what sampling techniques are commonly used in health care research. Some common sampling techniques used in health care include random sampling, stratified sampling, and cluster sampling. To answer this question, you can think about situations in which these techniques would be useful. For example, if a researcher wants to understand the prevalence of a disease in a specific population group (e.g., young adults), using stratified sampling may be appropriate. Another example might be when studying the impact of a healthcare intervention on hospitals, and cluster sampling could be used to select representative hospitals for the study.
B. When determining which sampling technique to use over another, you need to consider the specific research question and the characteristics of the population you want to study. Each sampling technique has its own advantages and disadvantages. For instance, random sampling provides a way to obtain a representative sample of the population, but it may not be feasible or practical if the population is large or geographically dispersed. Stratified sampling, on the other hand, allows for more precise representation of specific subgroups within the population but can be complex and time-consuming.
C. To state the drawbacks of each sampling method, you can research and consider the limitations associated with each technique. For example, random sampling can be costly and time-consuming if the population size is large. Stratified sampling may require detailed knowledge about the population ahead of time, which may not always be available. Cluster sampling can introduce clustering effects and may have limited generalizability to the entire population.
In summary, answering these questions requires understanding the different sampling techniques, considering the specific research context, and examining the advantages and disadvantages of each method.