All examples for Correlation Matrix Generator

Customer Satisfaction Survey Heatmap

Correlation heatmap for customer survey data with Likert scale ratings (1-10). Analyzes relationships between product quality, service, shipping, price value, and overall satisfaction. Demonstrates handling of ordinal survey data with smaller sample sizes.

Input

What you provide to the skill

Correlation heatmap for survey scores: product_quality, service, shipping, price_value, satisfaction (85 responses, 1-10 scale)

Output

What the skill generates for you

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CORRELATION ANALYSIS RESULTS

Dataset: 83 rows x 5 columns
Numeric variables analyzed: 5
Variables: product_quality, service, shipping, price_value, satisfaction

Strong Correlations Found: 10 (|r| > 0.7)

product_quality <-> service r = 1.000 (positive)
product_quality <-> price_value r = 1.000 (positive)
product_quality <-> satisfaction r = 1.000 (positive)
service <-> price_value r = 1.000 (positive)
service <-> satisfaction r = 1.000 (positive)
price_value <-> satisfaction r = 1.000 (positive)
product_quality <-> shipping r = 0.939 (positive)
service <-> shipping r = 0.939 (positive)
shipping <-> price_value r = 0.939 (positive)
shipping <-> satisfaction r = 0.939 (positive)

Multicollinearity Issues: 10 (|r| > 0.8)

WARNING: High correlations detected between predictors!
Consider removing or combining these variables for regression modeling:

  • product_quality <-> service (r = 1.000)
  • product_quality <-> price_value (r = 1.000)
  • product_quality <-> satisfaction (r = 1.000)
  • service <-> price_value (r = 1.000)
  • service <-> satisfaction (r = 1.000)
  • price_value <-> satisfaction (r = 1.000)
  • product_quality <-> shipping (r = 0.939)
  • service <-> shipping (r = 0.939)
  • shipping <-> price_value (r = 0.939)
  • shipping <-> satisfaction (r = 0.939)

Output Files Generated:

Correlation Matrix: survey_scores_matrix.csv
Heatmap Visualization: survey_scores_heatmap.png

Correlation Matrix Heatmap