Whiche measure best represents data( in my case salaries) mean, median or mode?
Thanks
Does anyone know this answer?
Of the measures of central tendency, for a skewed distribution such a with salaries, the median is the most central of these measures.
To determine which measure best represents data, such as salaries, it's important to understand the characteristics of each measure: mean, median, and mode.
Mean: The mean, also known as the average, is obtained by summing up all the salaries and dividing it by the total number of salaries. It represents the typical value of salaries across all individuals. The mean is sensitive to extreme values or outliers. If there are extreme salaries, such as a few very high or very low salaries, they can significantly affect the mean and may not accurately represent the general salary range.
Median: The median is the middle value of the sorted salary data. It represents the value that separates the higher half from the lower half of the data. Unlike the mean, the median is not influenced by extreme values. It is a better measure of central tendency when dealing with skewed distributions or outliers.
Mode: The mode represents the most frequently occurring salary value in the data. It is useful when you want to identify the salary category that appears most often, such as identifying the most common salary range or job position. However, the mode may not be sufficient if you are interested in the distribution or the average value of the salaries.
Determining which measure is best will depend on the characteristics of your data and the specific question you want to answer. If you are interested in the general tendency of salaries and want to consider extreme values, the mean might be appropriate. If you are concerned about extreme values and outliers, the median is a more robust measure. If you want to identify the most common or frequently occurring category, the mode would be suitable.
Consider the context and purpose of your analysis to decide which measure will best represent your data. Sometimes, it is also useful to consider a combination of these measures to gain a more complete understanding of the salary data.