Random Sampling Essay

added to the limitations of the method. It could be argued that random sampling would provide a

This sample may have a bias resulting from subjects that have a special interest in the subject being studied.

When researchers select participants from several different parts of the population, they are selecting a

Lind, D. A. (2005). Statistical Techniques in Business & Economics (12 ed.). New York: The

a. A large non-random sample can turn out to be unrepresentative if the data is non-random. By selecting non-random of population members, then the entire population does not have the chance to being selected.

There are 3000 students at my school. For this experiment, I decided that using a sample size of 40 students will be feasible and fairly representative of the entire population. In order to try and insure that this sample best represents the school, it is important to carefully choose a sampling method which decreases any chance of bias. Originally, I wanted to use a simple random sample which would give everyone in the school an equal chance of being chosen, therefore making the results fair and not directed towards a certain group of individuals. However, getting a hold of a list of all students in the school that I can use to randomly select my sample group was not realistic. So, I decided that a voluntary response sample would be more practice in this situation. Not only does using this sample make the process less time consuming and convenient, but it also solves the problem of not being

A. Sampling is a selection of a smaller percentage of individuals from within a larger population that is used to estimate the attitudes and characteristics of the whole population. Sampling saves time and money which is always a good thing, and allows for more manageable research. It may be almost impossible to identify every member of a population/group some may be too large, for example, if you were conducting a study on high school students as to whether they bring lunch to school or eat at the cafeteria, and this research was conducted for the entire state of Texas. Well, it would take an enormous amount of manpower and money to survey every single high school student in the state plus you would have other factors to consider as well. Then you would run into managing issues with such a large endeavor, so choosing a sample or small representation of individuals from the larger population is more

2. a) The study used a consecutive non randomized, non-probability sampling method. The study selected records of patients admitted to the Massachusetts General Hospital (MGH) between September 1997 and August 2008 in a consecutive manner until a specific number was obtained. In this study, the number was 297. The study excluded 62 records that did not fit the sampling requirements. The final sample was n = 235 (Salinas et al., 2012). When using consecutive sampling techniques, the researcher includes all patients who agree to participate, provided that they meet specific pre-established criteria. The researcher will stop the selection process when the desired sample is achieved. This sampling technique is similar to the convenience sampling technique except, that it aims to represent the whole cohort of the population (Fain, 2013). It is considered the most reliable non-probability sampling technique. This sampling method is more credible and possesses a higher validity level than any other non-probability sampling method. It also decreases the possibility of researcher’s bias. However, this sampling technique faces the same issue of all the non-probability sampling techniques as the possibility of bias is always present (Fain, 2013). Another drawback of the consecutive sampling technique lies within the possibility that the response rate and the type of individuals responding may influence the findings. The responding individuals may have life circumstances or personal

Pro: Cluster sampling is good for many different reasons, the first and most prominent being that the sampling technique is quick, easy, and cheap. Rather than sampling the entire population of Australia, the researcher can quickly and effectively conduct the research by choosing a few, randomly selected clusters.

Examiners are not interested just in the reactions of those surveyed; as an alternative, they seek out to define the greater population from which the sample was

According to Hair et al. (2003), in the research, the sampling process enables identifying, developing and understanding an interested object that need to be determined (p.333). Hence, in order for the researcher to carry out the sampling appropriately, advantages and disadvantages of the various sampling methods should be considered along with the theoretical component of the study (Hair et al. 2003, p. 368 f). Theoretically, the sampling procedure is divided into two major types which consist of probability and nonprobability sampling. In probability sampling, individuals have a known chance of being selected. While, in non-probability sampling, individuals do not have a known possibility to be selected (Sekaran 2003, p. 269 f). Also, the different sampling methods provide different advantages and disadvantages. Hence, the researcher should consider this point before choosing the sampling method for the

Sampling is taking a few items from a population that fairly represent the population to obtain information about the population from them. It is usually one of the key steps in research because it determines the validity and reliability of research results. This crucial yet arduous task in research has led statisticians and software developers to create software that can ease this process for many researchers in various fields of study. An example of such a sampling software is the Visual Sample Plan version 7.0 (VSP 7.0).

Stratified random sampling: can be described as a way of making sure that specific strata or categories of people are represented in the sampling process (Mathers, Sampling for surveys, 2009).

Sampling techniques provide a range of methods that enable the researcher to reduce the amount of data that needs to be collected by considering only data from a subgroup rather than all possible cases (Saunders et al., 2007:204). The researcher collected data from the identified population in a company where the researcher was employed in the payments department and IT provided technological solutions to the business unit.

* Appropriate sampling: There are so many different methods of sampling. It of a top priority to choose the right one based on budget constraints and efficiency