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QuantumXl 2013

Correlation and Covariance

 

Pearson's and Spearman's Correlation Coefficient

Find the time series tools under the QXL Stat Tools tab -> Analysis Tools ->  Correlation and Covariance.

 

Pearson's Correlation Coefficient is a measure of the strength and direction of a linear relationship between two variables. Spearman's Correlation Coefficient is similar to Pearson's, but is calculated on the rank of the data instead of the actual value. Some researchers prefer to use Spearman's when the data isn't normal.

 

Correlation coefficients must fall between +1 and -1, where +1 indicates perfect positive correlation, -1 indicates perfect negative correlation, and 0 indicates no correlation.

 

Example Pearson's Correlation Coefficient Analysis

Pearson's Correlation Example

 

 

 

Example Spearman's Correlation Coefficient Analysis

Spearman's Correlation Coefficient

Covariance Analysis


Covariance is a measure of how much two variables change together. Positive values indicate a positive correlation while negative values indicate a negative relationship. The Correlation Coefficient (above) is a normalized version of the Covariance making the interpretation easier. The covariance of a variable with itself is also called the variance.

Example Covariance Analysis

Covariance Example