"Accuracy in statistics tells you how close your sample statistic is to a population parameter"
Statistics and Parameters
In order to understand accuracy, you must know the difference between a statistic and a parameter. This article explains the difference between a statistic and parameter in depth. However, the short explanation is that a parameter refers to an entire population, while statistics refers to a sample, or small percentage of an entire population. For example, if you survey a particular school to find out if they support the school team, it’s possible to ask every student in the school. You might find that 70% of students support the team. Because you asked every member of the population (the student body at that school), you have a parameter. However. if you wanted to find out how many U.S. students liked their school team, it wouldn’t be practical to ask every student (there are millions of U.S. students!) so you would only want to survey a small number of them. You would end up with a statistic.
Accuracy
Accuracy describes how close your statistic is to a particular population parameter. For example, you might be studying weights of pregnant women. If the sample median of your population is 150 pounds and your sample statistic is 149 pounds, then you can make a statement about the accuracy of your sample.
