When should I use a q-q plot?

Checking if data follows a normal distribution ● Comparing two distributions ● Statistical diagnostics

When should I avoid a q-q plot?

Non-technical audiences ● When distribution shape is the primary story ● Fewer than ~10 data points (the line is unreliable)

What are common mistakes with q-q plots?

Misinterpreting deviations from the reference line ● Too few data points for meaningful comparison

Distribution

Q-Q Plot

Compares a distribution against a theoretical distribution (e.g. normal) point by point.

Normal Q-Q Plot

Checking normality of 50 exam scores

View data (50 rows)

Chart data table: Normal Q-Q Plot
Value
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Make a q-q plot with your data

Use a q-q plot when…

Checking if data follows a normal distribution
Comparing two distributions
Statistical diagnostics

Avoid when…

Non-technical audiences
When distribution shape is the primary story
Fewer than ~10 data points (the line is unreliable)

Data it needs

Property	Value
Min Rows	10
Min Columns	1
Column Types	number

Visual anatomy

Marks

circleline

Channels

position-xposition-y

Axes

x-theoretical quantilesy-observed quantiles

Guiding principles

Common mistakes

Misinterpreting deviations from the reference line
Too few data points for meaningful comparison

History

Developed by Wilk and Gnanadesikan in 1968 for distribution comparison.

Accessibility notes

Provide a mean / median / skewness / kurtosis summary table as the text alternative — generic 'summary statistics' alone underspecifies the diagnostic.

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