In business, statistics equations can be used to help investors or other business professionals to make well-informed decisions about the relationships between variables. The correlation coefficient (R) and the coefficient of determination (R-Squared) are two numbers that help investors to better understand the relationship of two variables when placed in the same situation. By understanding these coefficients, an investor can determine the statistical chances that an investment is good or bad.

What Do These Coefficients Measure?

These two coefficients are used to measure the strength of a relationship between two variables. For example, an investor will want to know if investing more money into a situation will increase their rate of return. By using these two coefficients, that investor can get good statistical indicators on whether or not the relationship is solid and if it will last very long.

Correlation Coefficient (R)

The R coefficient measures the relative strength between two variables. There are many different ways of calculating R, but the most common is referred at as Pearson’s coefficient calculation. In many statistical circles, Pearson’s computation is considered the standard for the R coefficient.

The R coefficient is measured in terms of negative one, one and zero. When the R coefficient is one, then a positive change in the first variable will create a positive change in the other. An R coefficient of negative one means that a positive change in the first variable creates a negative change in the other. When the coefficient is zero, then there is no relationship.

The strength of the coefficient depends on how close it is to one or negative one. One is the absolute best and negative one is the absolute worst. The numbers in between indicate the degree to which the relationship is weak or strong.

R-Squared

To calculate R-squared, you would square the R coefficient and then multiply by 100 to get a percentage. The best way to understand R-squared is to look at it like data points on a graph. When you put a straight line on the graph, that line is going to pass through some of those data points. The more data points your line passes through, the more accurate your R coefficient information will be.

When the R-squared is expressed as a percentage, it is the percentage of data points that straight line passes through. The goal is to get all of the data points to line up in a straight line for maximum accuracy. But the R-squared coefficient will tell you what percentage of data points are actually on the line. The higher the percentage, the more likely the R coefficient is correct.

Statistics is a discipline that is treasured by investors and many other types of business professionals. When you use statistical tools such as the R and R-squared coefficients, you can get a better picture as to whether or not an investment is a good or bad idea.