Residual Plot
Definition
A residual plot shows the differences between observed and predicted values in regression analysis. It helps identify patterns or trends in these differences, indicating whether linear regression assumptions are met.
Analogy
Think of baking cookies using a recipe with specific measurements for ingredients. The residual plot is like comparing the actual size of each cookie to the expected size based on the recipe. If most cookies are close in size, the residuals will be small and random. However, if some cookies turn out much larger or smaller than expected, there may be a pattern or issue with the recipe.
Related terms
Regression Analysis: Regression analysis is a statistical method used to model and analyze relationships between variables.
Homoscedasticity: Homoscedasticity refers to the assumption that the variability of residuals is constant across all levels of predictor variables.
Linearity: Linearity assumes that there is a linear relationship between predictor variables and the response variable in regression analysis.
"Residual Plot" appears in:
Study guides (2)
Practice Questions (5)
- What does a residual plot help us determine in a t-test for the slope?
- What does it mean when a residual plot exhibits apparent randomness?
- What does it indicate if a residual plot shows an apparent curved pattern?
- What is the main purpose of a residual plot in linear regression?
- What can be inferred from a residual plot showing a U-shaped pattern?
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