The sample mean and sample proportion are both statistical measures used to summarize data, but they represent different concepts and are calculated in distinct ways.
The sample mean is the average of a set of numerical values. It is calculated by adding all the values together and then dividing by the number of values. For instance, if you have a sample of test scores from a class, the sample mean would give you the average score of those students.
On the other hand, the sample proportion represents the fraction or percentage of observations in a sample that possess a certain characteristic. It is calculated by dividing the number of favorable outcomes by the total number of observations. For example, if you’re surveying a group of people to see how many of them prefer coffee over tea, the sample proportion would be the number of coffee lovers divided by the total number of respondents.
In summary, while the sample mean deals with averages of quantitative data, the sample proportion focuses on the ratio of a specific category within a categorical dataset.