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In the field of statistics, positive correlation describes the relationship between two variables which change together, while an inverse correlation describes the relationship between two variables which change in opposing directions. Inverse correlation is sometimes described as negative correlation, which describes the same type of relationship between variables.

Examples of positive correlations occur in most people's daily lives. The more hours an employee works, for instance, the larger that employee's paycheck will be at the end of the week. The more money is spent on advertising, the more customers buy from the company.

Inverse correlations describe two factors that seesaw relative to each other. Examples include a declining bank balance relative to increased spending habits and reduced gas mileage relative to increased average driving speed. One example of an inverse correlation in the world of investments is the relationship between stocks and bonds. As stock prices rise, the bond market tends to decline, just as the bond market does well when stocks are underperforming.

It is important to understand that correlation does not necessarily imply causation. Variables A and B might rise and fall together, or A might rise as B falls, but it is not always true that the rise of one factor directly influences the rise or fall of the other. Both may be caused by an underlying third factor, such as commodity prices, or the apparent relationship between the variables might be a coincidence.

The number of people connected to the Internet, for example, has been increasing since its inception, and the price of oil has generally trended upward over the same period. This is a positive correlation, but the two factors almost certainly have no meaningful relationship. That both the population of Internet users and the price of oil have increased is likely to be a coincidence.

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