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# What is a real life negative correlation example?

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An example of a negative correlation in practical terms is that as a chicken gets older, they tend to lay fewer eggs. This is a negative correlation because as the years of the chicken increase, the number of eggs decrease, meaning that the two numbers are moving opposite from each other.

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Credit: Open Data Institute CC-BY-SA 2.0

A negative correlation happens when two variables have an inverse relationship. They do not travel on the same planes, and the second variable is affected by the first variable. One variable will increase in value, while the other one decreases as a result of the increase in value. Negative correlations can also happen when one variable decreases in value, causing the other variable to increase in value.

A positive correlation is opposite of a negative correlation in that the second variable is directly affected by the first variable. As the first variable increases or decreases, the second variable will increase or decrease in accordance with the first. If this were applied to the practical example of negative correlation, a chicken would begin to lay more eggs as its number of years increased. The numbers that are present within either a positive or negative correlation list the strength that the correlation has in the example.

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## Related Questions

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Cramer's V is a chi-square based method of determining correlation in tables with more than 2x2 rows and columns, according to ChangingMinds.org. It is used to determine the strength of a correlation that has already been deemed significant by a chi-square test.

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To find the derivative of a given function, plug the function into the derivative formula, distribute all of the terms, and then cancel all possible terms to eliminate the formula's denominator. Once the formula is simplified, set h to approach zero to find the derivative.

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Sample mean is calculated by finding the sum of all terms in the selected sample and dividing this figure by the total number of terms. This formula is used to compute the average of the data collected.