Similar to the sample mean, the sample mode is a measure of the location or center of a statistical distribution. However, instead of calculating the average of a set of observations, the sample mode calculates the most frequently occurring value in a sample.
To calculate the sample mode, you need to identify the value that occurs most frequently in your sample. 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 mode is 2 because it occurs more frequently than any other value in the sample.
It is important to note that a sample may have more than one mode if two or more values occur with the same frequency. For example, if you have a sample of 10 observations with values of 2, 4, 6, 8, 10, 10, 14, 16, 18, and 20, both 10 and 2 are modes because they occur twice in the sample.
The sample mode provides information about the most frequently occurring value in a sample. This can be useful in a variety of applications, such as identifying the most common response to a survey question or the most popular product sold by a company.
However, it is important to note that the sample mode may not be representative of the overall population mode. Like the sample mean, the sample mode is not necessarily a robust statistic and can be greatly influenced by outliers or small sample sizes.
By understanding how to calculate and interpret the sample mode, you can gain valuable insights from your sample data and make more informed decisions.