In theory, as stock prices rise, the bond market tends to decline, just as the bond market does well when stocks are underperforming. In statistics, positive correlation describes the relationship between two variables that change together, while an inverse correlation describes the relationship between two variables which change in opposing directions. It can be assumed in general that if a particular person is involved in almost all of the meetings of a company then he/she is more valuable to the company. This shows that there exists a positive correlation between the time a person spent in the office meetings and his/her value in the company. Well, the vice-versa is also true, one can anticipate the number of meeting he/she will have to attend in the future if he/she knows his/her value in the company. One can even analyze the designation of a particular person in the company by observing the amount of time that the person spent in the official meetings.

This indicates that adding the stock to a portfolio will increase the portfolio’s risk, but also increase its expected return. There exist a negative correlation between the time spent running and the body fat of the person, i.e., the more time the person will spend running, the lesser will be the bodyweight of the person. Students, teachers and administrators see examples of positive correlations in schools every day. The more hours an employee works, for instance, the larger that employee’s paycheck will be at the end of the week. Instead, it is used to denote any two or more variables that move in the same direction together, so when one increases, so does the other.

## What Is an Example of Positive Correlation?

The person can also anticipate his/her performance in the company by observing the increase or decrease in the time he is involved in the meetings. One example of positive correlation is the relationship between https://accounting-services.net/what-are-operating-expenses/ employment and inflation. High levels of employment require employers to offer higher salaries in order to attract new workers, and higher prices for their products in order to fund those higher salaries.

A positive correlation is a relationship between two variables that move in tandem—that is, in the same direction. A positive correlation exists when one variable decreases as the other variable decreases, or one variable increases while the other increases. Because these two different variables move What is an everyday example of a correlation in statistics? in the same direction, they theoretically are influenced by the same external forces. When two variables vary in the opposite direction, i.e., if one variable increases the other variable decreases, or if one variable decreases the other variable increases, this is known as the negative correlation.

## Common Examples of Positive Correlations

Though this does not mean that one variable directly impacts the outcome or changes to the other, both variables always move in tandem and are most likely highly related. The most common way to determine a positive correlation is to calculate the correlation coefficient. This statistical measurement calculates the strength of the relationship between two variables. In statistics, a perfect positive correlation is represented by the correlation coefficient value +1.0, while 0 indicates no correlation, and -1.0 indicates a perfect inverse (negative) correlation. The boiling point of freshwater is different from the boiling point of water that contains impurities due to the colligative properties of the solvents.

Similarly, a rise in the interest rate will correlate with a rise in interest generated, while a decrease in the interest rate causes a decrease in actual interest accrued. Correlation studies can help the census surveys to analyze the association of great infrastructure say big parks, open areas, and other recreational areas in the building and the nearby areas, with sales of the apartments. Of course, this is a positive correlation as the better the infrastructure the more buyers will be interested to buy apartments in that area, i.e., the more will be the sales of the apartments.

## Beta and Correlation

The more and more impurities will be added to the freshwater the more will be its boiling point. If you observe the increase in the boiling point of the water coming into your homes through taps, you can well imagine the quality of the water. This means that there is a positive correlation between the boiling point of the water and the increase in the impurities. Drinking water should be of the consistent quality (constant boiling point) over time, i.e., there should be zero correlation between the boiling point of the water and the time elapsed. Correlation does not require causation, and it is a common logical fallacy to believe otherwise. When two variables are positively correlated, that does not necessarily mean that one variable causes changes in the other.

For most investors, an ideal investing strategy is to avoid positive correlation between assets and asset classes. Though every individual should evaluate their own investing strategy, holding assets with positive correlation tends to increase the risk of loss. Modern portfolio theory is heavily rooted in diversification, the concept that an investor should hold assets that are widely unrelated to reduce portfolio-wide risk. This flies in the face of positive correlation; investing theory usually states that investors should be wary of widespread positive correlation within their portfolio.