Quick Insights for Generalized Correlation | AO Easy Answers

Intended audience: end-users data science developers

AO Easy Answers: 4.3

Overview

The Generalized Correlation Insight generates a Correlation Heatmap for the series selected.

Assess the strength and direction of the relationship between two continuous variables.

Understanding the relationship between customer satisfaction scores and repeat purchases.

A business wants to know if higher customer satisfaction correlates with increased repeat purchases.

A strong positive correlation indicates that improving satisfaction could lead to more repeat business.

Customer_Satisfaction_Score	Repeat_Purchases
4.37	1.24
9.56	8.30
7.59	9.96
6.39	8.61
2.40	4.97
2.40	1.18
1.52	4.80
8.80	11.32
6.41	4.76

Label	UI	Default	Description
Series	Checkboxes		Select which of the Series in the Chart shall be included in the Correlation.
Correlation Model	Dropdown		Select the model to use for the correlation. Robust can only be used for continuous series, but is more resilient to outliers in data. Pearson - the Pearson correlation measures the strength of the linear relationship between two variables. Robust (for continuous series) - the Robust (Bayesian) correlation will provide more accurate estimates even when outliers exist in the data.

Label

Default

Description

Series

Checkboxes

Select which of the Series in the Chart shall be included in the Correlation.

Correlation Model

Dropdown

Select the model to use for the correlation. Robust can only be used for continuous series, but is more resilient to outliers in data.

Pearson - the Pearson correlation measures the strength of the linear relationship between two variables.
Robust (for continuous series) - the Robust (Bayesian) correlation will provide more accurate estimates even when outliers exist in the data.