Read the discussion which is given below and give response:
Sampling is an effort to identify information about a larger population based on the sample utilized for the specific research study. In order to appropriately display the population of intended study, it is imperative that the sample is framed in a manner that eliminates error, correctly represents the population as well as develops data that can be utilized effectively in application. "The sampling frame is closely related to the population. It is the list of elements from which the sample is actually drawn" (Cooper & Schindler, 2014, p.347). We recognized and know that the sample is simply a representation of the population and for that reason must be designed (framed) in a manner that adequately eliminates error. Because there are multiple methods in which sampling can be conducted, there is also specific sampling frames that can be utilized in order to eliminate error. Utilizing Exhibit 14-8 from the assigned reading, the following will discuss the probability sampling designs and address how sample framework compares and differs for each in regards utilizing them for the hiring process within the military aviation industry. As an employer looking for new hires of employees, it is essential to make your hiring decisions based on assessments of potential future employees in comparison to a likely pre-defined criteria as well as an assessment of current employees skills utilized within the industry. Specific to military aviation, considerations could include experience level (defined by total time), upgrade experience (wingman, flight Lead or instructor pilot), combat time as well as previously held attached duty positions. Utilizing the above as criteria for a list of population elements, implementation of several of the sampling designs is available. Additionally, utilizing a program designed by the air force known as HARMS; collection, processing and presentation of the above discussed population is available to any requestor for groups of pilots, individual pilots as well as entire squadrons or wings of pilots in numerical data form. With this data and sampling frame available, the follow-on discussion would simply be which design provides the most efficient and accurate representation of employee skills is needed for hire. Speaking to the specific sampling designs, simple random could be effortlessly selected for the design based on the amount of data available utilizing the HARMS system. Disadvantages of simple random design defined by Cooper and Schindler include listing of population elements, larger sample sizes required and production or large errors; the first two disadvantages are no issue when utilizing the HARMS system and the latter could be reduced by effective discrimination of outliers (attached pilots - those who do not adequately represent flying population). Looking at a systematic design and selection, there would be concern of a potential result biased starting based on similarity in training processes. To prevent this bias, a cluster design could be utilized; by clustering based on upgrade experience, the employer could assess differences of population elements based on the level of upgrade completion (which characteristically is related to overall experience). This would pool the data in a manner that would provide unbiased estimates of population parameters (Cooper & Schindler, 2014). The only other two options for sampling design include stratified and double. Of the two, utilization of HARMS would be effective in that the data is available, and application of the data is the only consideration. Speaking to stratified specifically, using any of the above discussed population elements could effectively define the population into sub-populations and provide statistical efficiency. Double would also be effective, assuming the initial sample (cluster sample) was effective and provided actionable data, to then follow up with a sequential sampling.