Definition: The "law of large numbers" is a principle in statistics that states that when you take a large number of random samples from a population, the average of those samples will get closer to the average of the entire population. In simpler terms, if you do something many times, the results will start to show the true average.
Imagine you want to know the average height of students in your school. If you measure just a few students, your result might be very different from the true average height of all the students. However, if you measure the heights of 100 students instead of just 5, the average you calculate will be much closer to the actual average height of everyone in the school. This is an example of the law of large numbers in action.
In more advanced statistics, the law of large numbers helps in making predictions and decisions based on data. It is foundational for fields like economics, psychology, and any area that relies on statistical analysis.
The "law of large numbers" specifically refers to statistics and does not have different meanings outside this context.
In short, the law of large numbers tells us that larger samples provide more reliable estimates of population characteristics.