Business Research Methods, Part III In an effort to remain a vigilant thriving organization, Wal-Mart must have been active in creating satisfied customers. Without customers Wal-Mart will suffer in all areas that allow the organization to continue to be strong. In surveying employee, several reasons for mediocre performance that influences customer behavior were identified. In this research, several aspects will be revealed. Based on the survey, potential challenges to validity and reliability will be discussed, steps needed to minimize the challenges will be outlined, the data will be presented in an appropriate general response type, and the findings will be classified in order of power.
Potential Challenges
In our research project, there is a possibility or potential for challenges to validity and reliability in our research question, data, and analysis. Validity is an important aspect of our research question, data, and analysis. Validity has been defined by Cooper as, “the degree to which the instrument measures what it’s supposed to measure. If an instrument is not reliable over time, it cannot be valid, as results can vary depending upon when it is administered. An instrument can be neither reliable nor valid, reliable and not valid or both reliable and valid. However, an instrument must be reliable in order to be valid” (Cooper, 2011). Making sure that our research question, data, and analysis are valid is important because we need to make sure that what we are measuring is being measured properly and as precisely as possible. The reliability of our research question, data, and analysis is important because we need have similar results under varying conditions. Cooper states that, “reliability determines how consistently a measurement of skill or knowledge yields similar results under varying conditions. If a measure has high reliability, it yields consistent results. There are four (4) principal ways to estimate the reliability of a measure: 1) Inter-observer, 2) Test- Retest, 3) Parallel- Forms, 4) Split- half reliability” (Cooper, 2011). To have reliable information is very important to our research question, data, and analysis because we need to be able to have similar results under the different conditions that are presented. A potential challenge that might be encountered is that of achieving an accurate relationship between the data and the conclusion. This can create a challenge because if the data doesn’t support or prove the conclusion, then the research question, data, and the analysis because unreliable and invalid. We need to be careful and certain that the data and the conclusion have an accurate relationship and correspond with each other accurately. Accuracy of the data will help create the necessary validity and reliability we need for our research question, data, and analysis.
Steps to Minimize Challenges
While gathering our data for our research question, we have realized that achieving an accurate relationship between the data and conclusion can be a challenge we could possibly encounter. In order to achieve and maintain an accurate relationship between the data and the conclusion, we must: check for relevancy, specify treatment levels, control the environment and extraneous factors, choose the appropriate experimental design, draft and revise design, and finally analyze (Cooper & Schindler 2011). The type of data used for the general response should be relevant to the research question posed. Data used that is clear and closely related to the research question will prevent results that would otherwise yield a false and unreliable response. Treatment levels must be specified and simple, to ensure accurate data collection at appropriate sized intervals. Controlling the environment and extraneous factors such as location, shift, and department will provide the consistency needed for accurate results. Choosing the general response type that is the most appropriate for the
