Use of Simulations for Teaching Professional Competencies

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CHAPTER 3: SAMPLING

Definition

A sample is defined as a collection of individuals who were selected for a research study (Frankfort-Nachmias& Leon-Guerrero, 1997, ppn.d), and the process of selecting the subset of these people from a statistical population is known as sampling. Sampling is performed to estimate the characteristics of the entire statistical population. There are several stages in a sampling process such as, defining the population, specifying a sampling frame, specifying a sampling method, determining the sampling size, implementing the sampling plan, and lastly sampling and data collecting. Focused problem definition is the key to successful statistical practice, which include efficiently defining the population form which the sample will be drawn for research. Furthermore, the main goal is to define a subset or representative sample from that population in order to achieve successful statistical results of the characteristics of entire population. There are many advantages of sampling which include, lower costs of the research process, faster data collection for the research and higher accuracy, quality, and homogeneity of the data set.

Why Sample

If the research study requires information about a particular population in order to know the desired characteristics of that population, through testing or questioning, there could be two simple options:

Every individual of the particular population can be tested or questioned, or

A selected number of individuals can be selected, as a sample, for questioning or testing.

Contacting, testing, questioning and obtaining information from a relatively large population could be extremely difficult, expensive and time consuming. For instance, questioning and testing of 10,000 trainee professionals for determining the use of simulations for teaching professional competencies will be an extremely difficult, expensive and time consuming task. However, dividing this population into a properly designed small sample will aid in inferring the right and reliable information of the population. Sampling is also useful because usually researchers are conducting research in a limited time frame, which requires limiting the number of population to easily approachable sample in a given time. Hence, a sample may provide reliable information with a very small margin of error, when conducted properly. Research suggests that the most desired and accurate sample for any given research study is the probability sample (Sudman, 1976, pp. n.d). Random sampling is employed in probability sample in order to ensure equal probability of selection method. Members of population are analytically but randomly selected form the carefully defined population for performing the testing.

Sampling Approaches Overview

Sampling approaches are generally classified into probability sampling and non-probability sampling.

Probability sampling is more costly to conduct; however, the results are also accurate (Cohen, et,al. 2007, pp. 110-111). The possibility for selecting each individual from the sample is known to the researcher. In non-probability sample the researcher does not know the chance for including the exact individual in the sample. Moreover, probability samples also allow the study's findings to be generalized from the sample to the population. However, non-probability samples findings are only limited to the individuals or elements ...