4.7: Q-Q plot
- Page ID
- 45038
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Use of graphs by a data analyst may serve different purposes: communication of results or as diagnostics. The Q-Q plot is one example of a graph used as a diagnostic.
The quantile-quantile, or Q-Q plot, is a probability plot used to graphically compare two probability distributions. In brief, a set of intervals for the quantiles is chosen for each sample. A point on the plot represents one of the quantiles from the second distribution (y value) against the same quantile from the first distribution (x value).
A common use of Q-Q plot would be to compare data from a sample against a normal distribution. If the sample distribution is similar to a normal distribution, the points in the Q–Q plot will approximately lie on the line \(y = x\).
R code
In R, the Q-Q plot can be obtained directly in Rcmdr.
Rcmdr: Graphics → Quantile-comparison plot…
After choosing the variable (in this case, Sales), click on Options tab and make additional selections before making the graph. Here, we selected normal distribution.
Another version is available in the KMggplot2 package.
Questions
- What is a Q-Q plot used for in statistics?
- Looking at the plot in Figure \(\PageIndex{1}\), explain why the confidence lines get further and further away from the straight line.