The emergency department usually functions as the gateway to most acute care facilities. In a hypothetical study, it was found that the waiting times at the emergency department were long, leading to increased health risks, lack of treatment because patients leave without being attended to, overcrowding, and poor satisfaction among patients. From a study sample of 40 patients at the emergency department, the mean wait time for the sample was found to be 60 minutes and a standard deviation of 40 minutes. After computing for a confidence interval at 95 percent, the upper boundary was found to be 48.24 minutes and 62.18 minutes. A confidence level of 95% means that there is a five percent opportunity for being wrong (Polit, 2010). Therefore, the researcher is 95 percent confident that the average emergency department wait time at the acute health care facility is between 48.24 minutes and 62.18 minutes. Reducing the confidence level from 95 percent to 90 percent would translate to a narrower interval. When an increase in limits of a confidence interval happens, the interval with the precise mean has reduced reliability ( Choudhary & Garg, 2012 ).
Reducing a confidence level reduces the error boundary while widening the confidence interval. On the other hand, increasing the confidence level to 99% would widen the interval that contains the true mean. When a confidence level is increased, the error boundary increases too (Polit, 2010). As a result, the confidence level increases. Therefore, if the confidence level for the hypothetical study was increased to 99 percent, the 95 percent confidence interval of between 48.24 and 62.18 minutes would widen further. In addition, the error margin would reduce from 5 percent to one percent. However, it does not translate to an increase in respective accuracy. A 95 percent confidence level would be appropriate for the study because the data is normally distributed, and the sample size more than 30.
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References
Choudhary, D., & Garg, P. K. (2012). 95 % confidence interval: A misunderstood statistical tool. Indian Journal of Surgery , 75 (5), 410-410. https://doi.org/10.1007/s12262-012-0555-z
Polit, D. F. (2010). Statistics and data analysis for nursing research . Prentice Hall.
