Q-Q Plot
Chart overview
A Q-Q (Quantile-Quantile) Plot is a probability plot, which is a graphical method for comparing two probability distributions by plotting their quantiles against each other.
Key points
- It is primarily used to check if data follows a normal distribution.
- If the data is normally distributed, the points will fall approximately along a straight reference line.
Example Visualization
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"Create a Q-Q plot to check if the 'Residuals' of my regression model follow a normal distribution. Generate synthetic residuals (n=100) that are mostly normal but with heavier tails (t-distribution). Plot observed quantiles vs theoretical normal quantiles. Add a red reference line (45 degrees). Title: 'Q-Q Plot of Regression Residuals'. Label axes 'Theoretical Quantiles' and 'Ordered Values'."
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Python Code Example
Console Output
Plot displayed. R-squared value typically shown in title or console.
Common Use Cases
- 1Testing for normality
- 2Comparing two distributions
- 3Identifying outliers
- 4Model residual analysis
Pro Tips
Points on the line indicate normality
S-shaped curves indicate heavy/light tails
Check outliers at the extremes
Scientific Chart Selection Cheat Sheet
Not sure whether to use a Violin Plot, Box Plot, or Ridge Plot? Download our single-page reference mapping the most-used scientific chart types, exactly when to use them, and the core Matplotlib/Seaborn functions.