A sample needs to be random and if not a simple random sample of the whole population then a stratified random sample (there are different ways to stratify). Otherwise the study is a waste of time.
The only way to get rid of sampling error is to use the entire population under study. This is usually impossible, so the next best thing is to use large samples and good sampling methods.
Dan M. Guy has written: 'Wiley Practitioner's Guide to Gaas 2000' 'An introduction to statistical sampling in auditing' -- subject(s): Statistical methods, Auditing, Sampling (Statistics) 'Ethics for CPAs , Meeting Expectations In Challenging Times' 'Auditing/Study Guide' 'Practitioner's guide to audit sampling' -- subject(s): Statistical methods, Auditing, Sampling (Statistics)
Methodological rigor refers to the thoroughness and precision in the design, conduct, and reporting of scientific research. It involves using systematic and well-defined methods to ensure the validity, reliability, and reproducibility of study findings.
you can use sampling when your population under study is large, expensive and time time consuming to study.... in a nut shell, when studying entire population is expensive we go for sampling...
The methods section of a research paper is important because it outlines how the study was conducted, including the procedures, materials, and data analysis techniques used. This section is crucial for ensuring the study's credibility and quality because it allows other researchers to replicate the study and verify its findings. By providing a clear and detailed description of the methods used, researchers can demonstrate the rigor and reliability of their study, ultimately enhancing its credibility in the academic community.
The best way to reduce sampling error is to use random sampling in the study. This means selecting the population to study through a random process. This will ensure that each member of the population under study has an equal chance of being selected.
Secondary data may not answer fully answer the research questions of a study. It is also hard to establish its validity, and if proper sampling and data collection methods were employed.
cluster sampling, quota sampling, systematic sampling, stratified random sampling which one is correct?
The major source of sampling error is sampling bias. Sampling bias is when the sample or people in the study are selected because they will side with the researcher. It is not random and therefore not an adequate sample.
Sampling error occurs when the sampling protocol does not produce a representative sample. It may be that the sampling technique over represented a certain portion of the population, causing sample bias in the final study population.
The answer will depend on which study!
Casual studies are study methods that test a hypothesis in a market situation to better understand cause and effect relationships.