The mean is calculated by adding together all the values, and then dividing them by the number of values you have. Statistics for the Terrified discusses using symmetry to determine if the mean or median should be used in data analysis: So why would you use one over the other? It all comes down to the possibility of an outlier number skewing the result to be less representative of the “average” number. If there are two middle numbers, then take the average of the two middle numbers to obtain your median income. Median income is the middle number in the data set, which can be determined by placing all the numbers in value order and finding the middle number in the data set. To determine the average, add up all the numbers in the data set and then divide by how many numbers there are in the data set. The average (mean) income is the sum of a set of numbers divided by the count of numbers in the data set. It is important to understand the difference between average (mean) income and median income. An outlier is a value that "lies outside" most of the other values in a set of data and is much smaller or larger than in value. Should you use median income or average income statistics? Cubit’s Blog suggests the answer is to use median income data - either instead of or in addition to – average income data, because outlier data can skew the average.
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