Module 8. Correlation Analysis and ggplot2

 


From the patterns that can be seen in the regression model above, there is a strong, negative relationship between horsepower and miles per gallon. So, cars with higher horsepower will have lower gas mileage. The regression line clearly slopes downward, showing a consistent trend across all data points that confirms the negative correlation between the two variables. 

In terms of grid layout enhancing interpretation, while my visual focused on a single regression model, using a clean and evenly spaced layout supported readability and emphasis on the regression line. The structured design drew attention to the main pattern—how horsepower variable affected mpg—without unnecessary clutter or visual noise. In general, placing the scatter plots side by side in a grid layout makes it easier to compare how each factor can influence mpg. The consistent scales, neutral color palette, and aligned axes allow quick visual comparison without distraction. 

In my opinion, Few’s recommendations helped my design choices by keeping the visuals clean and focusing on the data. Using minimal colors, clear labels, and removing unnecessary chart elements made the regression trends more readable. Rather than adding extra decoration, the simplicity supports clarity—helping viewers interpret relationships directly from the patterns. 

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