What Empirical law of averages is
The empirical law of averages is a statistical concept that states that the average of a series of numbers will tend to approach the true average as the number of observations increases. In other words, the more observations you make, the more accurate your prediction of the average will be.
Steps for empirical law of averages:
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Identify the data that you want to measure the average of.
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Calculate the average by adding up all the observations and dividing by the number of observations.
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Increase the number of observations by taking more measurements or collecting more data.
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Recalculate the average.
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Compare the newly calculated average to the previous average.
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Repeat steps 3-5 until the difference between the two averages is negligible.
Examples
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The Law of Averages states that a large number of random events will tend to even out to an average result. For example, if you flip a coin multiple times, you can expect that the number of heads and tails will be roughly equal in the long run.
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The Law of Averages is often used when predicting the outcome of a sporting event. For example, if a team has scored an average of 3 goals in their last 10 games, it is likely that they will score around 3 goals in their next game.