Similar to the sample mean and sample mode, the sample median is a measure of the location or center of a statistical distribution. However, instead of calculating the average or most frequently occurring value in a set of observations, the sample median calculates the middle value of a sorted sample.
To calculate the sample median, you need to sort your sample in ascending or descending order and identify the middle value. If your sample has an odd number of observations, the median is the middle value. For example, if you have a sample of 9 observations with values of 2, 4, 6, 8, 10, 12, 14, 16, and 18, the sample median is 10 because it is the middle value in the sorted sample.
If your sample has an even number of observations, the median is the average of the two middle values. For example, if you have a sample of 10 observations with values of 2, 4, 6, 8, 10, 12, 14, 16, 18, and 20, the sample median is (10 + 12)/2 = 11 because it is the average of the two middle values in the sorted sample.
The sample median provides information about the middle value of a sample, which can be useful in a variety of applications, such as identifying the median income of a population or the median age of a group of people. Unlike the sample mean and sample mode, the sample median is not influenced by outliers or extreme values in a distribution.
However, it is important to note that the sample median may not be representative of the overall population median. Like the sample mean and sample mode, the sample median is not necessarily a robust statistic and can be greatly influenced by small sample sizes.
By understanding how to calculate and interpret the sample median, you can gain valuable insights from your sample data and make more informed decisions. Whether you are analyzing survey responses, sales data, or any other type of information, the sample median can help you identify the middle value of your sample and make meaningful comparisons.
