A sample is designed by collecting data from the target population which in this scenario would be the family practitioners who did not choose to specialize in pediatrics after graduation.
The population is defined as “the entire group that you want to draw conclusions about” (Bhandari, 2020). The population for the practitioners that did not choose pediatrics as their specialty includes the family practitioners who were qualified to specialize in pediatrics nationwide but did not choose that specialty after graduating from American Academy of Pediatrics.
Sampling frames is a way to put all possible sampling units together and “the specific group of individuals that you will collect data from” (McCombes, 2022). In this scenario, there is no list of the family practitioners that did not specialize in pediatrics, but samples could be collected from the graduates of many medical colleges in a specific area and gather those samples as one to get a sampling frame. The sampling frame can also be done by accessing the practitioners that are a part of a national association such as American Academy of Pediatrics and determine those who did not choose pediatrics as their specialty in a certain geographical area.
The sampling unit is either an individual or a company sample, which in this case is newly graduated family practitioners who did not specialize in pediatrics after graduation. A sampling frame that can be used would be cluster sampling which “is a probability sampling method in which you divide a population into clusters, such as district of schools, and then randomly select some of these clusters as your sample” (Thomas, 2022).