Sampling and Data Collection in Research
Dr. Annette Love
Sampling and Data Collection in Research
Sampling is one of many ways to conduct research in human service. It consist of one or more elements selected from a population. The manner in which we select elements for the sample has enormous implications for the scientific utility of the research based on that sample (Monette, Sullivan, & DeJong, 2011). In order to select a good sample, you must first decide what population you want to get the sample from. If you are not able to retrieve a good sample it can result in inaccurate conclusion.
A major reason for studying samples rather than whole groups is that the whole group is so large that studying it is not feasible (Monette, Sullivan, & DeJong, 2011). For example, if a human service worker wants to learn about pregnant women or some other large group of people it may be hard to study everyone in this group. Another reason for sampling is the information is more accurate from carefully drawn samples, than it would be if you studied the whole group. There are two types of sampling, probability and non-probability.
Probability sampling is a method of sampling that utilizes some form of random selection (Trochim, 2006). This means that the samples are retrieved in a process that gives everyone in the population an equal chance of being selected. There are five different methods of probability sampling which are simple random sampling, stratified sampling, systematic sampling, area sampling and estimating sample size. An example of probability sampling is when the telephone surveys randomly select people to call in order to take the survey. Non-Probability sampling is when the researcher does not know the probability of each population elements inclusion in the sample (Monette, Sullivan, & DeJong, 2011).There are also five methods of nonprobability which are availability sampling, snowball sampling, quota sampling, purposive sampling, and dimensional sampling. An example for non-probability sampling is conducting research on a veteran who is suffering from PTSD and want specific answers. Studying all veterans who suffer from PTSD would be difficult so instead research can be conducted on individuals. If a researcher wants to know about a veteran who suffers from PTSD because of personal trauma instead of PTSD from deployment, non-probability sampling can be conducted.
When selecting samples for human service research you should avoid being bias. Bias is defined as any tendency which prevents unprejudiced consideration of a question. In research bias occurs when “Systematic error is introduced into sampling or testing by selecting or encouraging one outcome or answer over others”. Bias can occur at any phase of research including study design or data collection, as well as in the process of data analysis and publication (Pannucci MD, & Wilkins MD MS, 2010). In order to avoid being bias researchers can make sure that the method that they are using will help eliminate sources of bias. Randomization can also help because it will provide the group that has been selected with the same chances of being influenced by the exact same bias. Data Collection There are four levels of measurement which are nominal, ordinal, interval, and ratio. Nominal measurement is basically categorizing the information or data that is retrieved like sex, ethnicity, and religion. Ordinal measurement is used to rank the information or data collected in order. Interval measurement is using a numerical scale to measure in intervals. Last but not least ration measurement has all the characteristics of interval measurement but with zero point as an absolute.
In research reliability and Validity is used which is categorized as scales of measurement. Reliability refers to a measure ability to yield consistent result each time it is applied (Monette,...
References: Monette, D. R., Sullivan, T. j., & DeJong, C. R. (2011). Applied Social Research. A Tool for the Human Services (8th Ed.). Retrieved from The University of Phoenix eBook Collection database.
Pannucci MD, C. J., & Wilkins MD MS, E. G. (2010, August). Identifying and Avoiding Bias in Research. Plast Reconstr Surg, 126(2), 619-625.
Trochim, W. M. (2006). Web Center for Social Research Methods. Retrieved from http://www.socialresearchmethods.net/kb/sampprob.php
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