Determining the best measure of central tendency largely depends on the data that one is analyzing. The characteristics of the data will determine the best measure of central tendency between the three main measures, which are mean, mode and median. Different factors come to play, especially regarding the nature of the data being analyzed. Different questions such as skewness of data, continuous or nominal data among other things are considered. This paper analyzes whether wait time to see a doctor is best measured by median.
In cases where the data is skewed, it is not appropriate to use the mean value. Skewness represents the ability of the data to be evenly distributed around the mean. If the data is not given in this fashion, then it is not appropriate to use the mean to find average the average value as the correct measure of central tendency (Lund Research, 2015). In the same vein then, it is possible that wait time can be affected by a different number of factors thereby being extremely high or extremely low. Therefore, it is satisfactory to say that it is not possible to accurately measure the central tendency using the mean. Where there are many patients, wait time can extend over a long period whereby low patient counts can see patients attended to in minutes.
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As a result, median is more appropriate for this measure. Furthermore, the median value is also preferred to mode. In response to the question, therefore, it would be more appropriate to work with the median as the best measure of central tendency as wait time data is likely to be skewed in nature.
References
Lund Research. (2015). FAQs - Measures of Central Tendency . Retrieved from Laerd Statistics: https://statistics.laerd.com/statistical-guides/measures-central-tendency-mean-mode-median-faqs.php
