Law of averages

The Law of Averages, also known as the Law of Large Numbers, states that the more samples are taken from a population, the more likely the sample mean will approach the population mean. This means that as the sample size increases, the average of the sample will come closer to the population mean.

The Law of Averages can be broken down into the following steps:

  1. Calculate the population mean: This is the average of all values in the population.
  2. Take a sample of the population: This sample should be large enough to accurately represent the population.
  3. Calculate the sample mean: This is the average of the sample.
  4. Compare the sample mean to the population mean: If the sample mean is close to the population mean, then the Law of Averages has been proven true.
  5. Repeat the process: If the sample mean is not close to the population mean, then repeat the process with a larger sample size. Eventually, the sample mean will approach the population mean.

Examples

  1. The law of averages states that in the long run, the proportion of heads and tails when flipping a coin will be equal.
  2. The law of averages suggests that in a large sample, the average score of a test will be close to the population mean.
  3. The law of averages states that when a large number of observations are made, the mean of a given set of data will tend to stabilize.