Exploring the Relationship Between Peroxide and FFA Levels in Data Analysis

Apr 5, 2024, 12:14 PM

What is the relationship between Peroxide and FFA?

To explore the relationship between Peroxide and FFA, we'll plot these two variables against each other. This will help us visually inspect if there's a correlation between them.
The scatter plot with a trendline (using ordinary least squares regression) indicates a relationship between Peroxide and FFA. However, the specific nature of this relationship (e.g., linear, nonlinear) and its strength are not clear from the visualization alone. Further statistical analysis would be required to quantify this relationship.

Perform regression analysis

The regression analysis between Peroxide and FFA yielded the following results:
  • Slope: 1.54
  • Intercept: -4.71
  • R-squared: 0.64
  • P-value: 0.017
  • Standard Error: 0.47
This analysis suggests a significant positive linear relationship between Peroxide and FFA. The R-squared value indicates that approximately 64% of the variability in FFA can be explained by the variability in Peroxide levels. The P-value suggests that this relationship is statistically significant.

conduct hypothesis test on the data, show significate level and graphical representation of the interaction

Summary of Findings

  • Regression Analysis: A significant positive linear relationship between Peroxide and FFA was identified. The regression analysis showed a slope of 1.54, an intercept of -4.71, an R-squared value of 0.64, indicating that about 64% of the variability in FFA can be explained by Peroxide levels, and a P-value of 0.017, suggesting statistical significance.
  • Hypothesis Testing: A two-sample t-test between Peroxide and FFA resulted in a T-Statistic of 0.023 and a P-value of 0.982. This high P-value indicates that there is not a statistically significant difference in the mean values of Peroxide and FFA across the samples.
  • Graphical Representation: The density plots for Peroxide and FFA show their distribution across the dataset. These plots help visualize the interaction and the significant overlap between the two variables, supporting the hypothesis test result that suggests no significant difference in their means.
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