On a dataset I had done Descriptive & Regression Model Analysis
Isra Islam
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Target Variable: MPG
Model Fit Metrics:
Multiple R: 0.99094212 (strong positive correlation)
R Square: 0.981966286 (98.2% variation explained)
Adjusted R Square: 0.979142015 (strong model fit)
Model Significance:
F Statistic: 3503.05902 (high value, low p-value, model is significant)
Key Findings:
Strong model fit and significant variables.
Coefficients indicate the direction and magnitude of relationships.
Q8: Regression Function
Equation:
MPG = -4.596 * Cylinders + 0.119 * ModelYear - 0.00393 * Displacement + 0.0836 * Horsepower + 0.8526 * Weight - 0.867 * Acceleration
Explanation: Coefficients show how each feature affects MPG.
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Posted Sep 23, 2024
Linear regression predicted vehicle MPG using attributes like weight, horsepower, and origin, providing insights to enhance vehicle design and improve fuel effi
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Data Visualizer
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Microsoft Excel
Microsoft PowerPoint
Isra Islam
Data Analyst | Excel Expert
Data Analysis using Excel
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