Interactive Residual Plot Generator
Effortlessly analyze the fit of your linear regression models with our interactive Residual Plot Generator. Visualize residuals to assess model accuracy.
Input Data
Enter comma-separated values for the independent variable (x), dependent variable (y), and predicted y values.
Residual Plot
About Residual Plots
A residual plot is a graph that displays the residuals on the vertical axis and the independent variable on the horizontal axis. Residuals are the differences between the observed values and the values predicted by a regression model. The plot helps in assessing whether a linear model is appropriate for the data. Ideally, in a good linear model, residuals should be randomly scattered around the horizontal axis, indicating that the model captures the linear relationship effectively and there are no systematic patterns in the errors. Patterns such as curves or funnels in the residual plot may suggest non-linearity or heteroscedasticity, implying that a linear model may not be the best fit, or that the variance of errors is not constant.
- Random Scatter: Indicates a good fit for linear regression.
- Patterns (curves, funnels): Suggests issues with the linear model assumptions.
- Outliers: Points far from the zero line may indicate influential data points.
Source: Wikipedia - Residual Plot