Using Excel's correlation function I get a correlation of -7% between data sets A & B. Data set C has a 92% correlation to A and an 84% correlation to B. How can C be strongly correlated to A and B, but A and B are slightly negatively correlated to one another?

What other tests can I perform to help me better understand the relationships between A, B & C?

**Contents**hide

#### Best Answer

You could make scatter plots of each with each.

As to how it is possible, imagine this:

a and b are entirely independent.

c = a + b.

So, we would have something like (in `R`

code; stuff following a # is comment)

`set.seed(1) a <- rnorm(100) b <- rnorm(100) c <- a + b cor(a,b) # - 0.0009 cor(a,c) # 0.68 cor(b,c) #0.72 `

### Similar Posts:

- Solved – How to generate two negatively correlated random series of numbers?
- Solved – Difference between dependent and correlated variables
- Solved – Simulating data based on correlation coefficient?
- Solved – How to Simulate Random Multivariate Correlated Data and Uncorrelated Data for a given correlation coefficient and P value in R?
- Solved – Adding new variables makes regression coefficients individually insignificant