Correlation Matrix

Correlation refers to any of a broad class of statistical relationships involving dependence. Familiar examples of dependent phenomena include the correlation between the physical statures of parents and their offspring, and the correlation between the demand for a product and its price. Correlations are useful because they can indicate a predictive relationship that can be exploited in practice.

The correlation matrix is symmetric because the correlation between Xi and Xj is the same as the correlation between Xj and Xi.

Tables and Views

ITV_ITEM_VALUE

This view contains the non-prorated charges and non-prorated discount information of an account’s current, future, and historical items.

Fields

MONTHLY_CHRG_AMT_ITV

This field shows the item’s recurring charge.

MONTHLY_RETAIL_AMT_ITV

This field shows the full charge amount from the base price plan.

MONTHLY_VALUE_AMT_ITV

Shows the item value amount.

The value in this field is determined by the following calculation: Charge amount minus the discount amount minus the customer discount amount.

Data Visualization

Quick Analysis

First, the charge amount has a 0.99 relationship with the value amount and a 0.91 relationship with the retail amount.

Second, the retail amount has a 0.9 relationship with the value amount.

Finally, the circles show as dark blue corresponding to the scale with a maximum allowable value of 1.

Conclusion

This matrix accurately visualizes the strength of correlations among the MONTHLY_CHRG_AMT_ITV, MONTHLY_RETAIL_AMT_ITV, and MONTHLY_VALUE_AMT_ITV variables from the OPS$MDC.ITV_ITEM_VALUE view.