Healthcare Health and Health Services

Question: Sampling is used to make a conclusion based on a selected subset of observation from the entire population of interest. Selecting only few from the desired population help reduce cost and damages. The difference between nonprobability and probability sampling is that nonprobability sampling does not involve random selection and the sample selected may be bias. On the other hand, probability sampling involves random nonbiased sampling and all have an equal chance of being selected. Simple Random Sampling To select n units out of N that has an equal chance of being selected using a table of random numbers or a computer randomly generated numbers generator to select our sample. (Example as mentioned in the text book the researcher sampling 400 patients from one year of patient records). Systematic Sampling This method is used for larger size. Know the n (sample size) that we want or need from our population 1 N. Cluster Sampling Stratified Sampling Answer: Sampling as a tool is used to indicate how much data is to be collected and how often it can be collected. Sampling defines the samples for quantifying a system, issue, process or problem. The advantages of sampling is to reduce the damages from improper selection of participants and the cost involved in the process (Creswell, 2013). In probability sampling every element in the sample population has a known non-zero probability of getting selected. In non-probability sampling the probability of any element being chosen is not known. In the first kind of sampling, random samples can be selected from the population where as in the second kind of sampling the characteristic of randomness is not there. Non-probability sampling is more appropriate when there is no exhaustive population list present (Bowling, 2014). Simple random sampling- subjects chosen entirely by chance. Systematic random sampling- subjects selected based on a system of intervals in a numbered population. Stratified random sampling subjects are chosen by division into smaller groups. Cluster sampling- subjects chosen by division into clusters. Convenience sampling- subjects are found easily. Quota sampling- subjectshave the same proportions of individuals as the entire population with respect to known characteristics. Purposive sampling- subjects are chosen on basis of expert judgment. Snowball sampling- subjects are inaccessible or hard to find. The researcher decides for the appropriate sample size for a given study by considering the following aspects: How much preciseness needs to be present How much sure does the researcher wants to be of the results How much variation is present in the population being studied References Bowling, A. (2014).Research methods in health: investigating health and health services. McGraw-Hill Education (UK). Creswell, J. W. (2013).Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.