The Normal plot is a graphical tool to judge the Normality of the distribution of sample data.
Select or enter the variable's name in the variable input field. Optionally, you may enter a filter in order to include only a selected subgroup of cases in plot.
- Q-Q plot: option to create a Q-Q (Quantile-Quantile) plot, see below.
- Test for Normal distribution: see the different Tests for Normal distribution.
The horizontal axis of the Normal plot shows the numerical values of the observations, and the vertical axis gives the relative frequency in terms of the number of standard deviations from the mean.
The horizontal axis of the Normal plot shows the observed values, and the vertical axis shows the corresponding expected number of standard deviations from the mean (z-score), based on the ranks of the observed values.
When the option Q-Q plot is selected, the horizontal axis shows the z-scores of the observed values, z=(x−mean)/SD.
A straight reference line represents the Normal distribution. If the sample data are near a Normal distribution, the data points will be near this straight line.
Example of Normal plot: probably a Normal distribution
Example of Q-Q plot: Probably not a Normal distribution
Test for Normal distribution
- To see the results of the test for Normal distribution, use the Graph info command.
- To show the results of the test in the graph's legend, you
- right-click in the graph
- select "Format legend"
- in the legend's dialog box the results of the test for Normal distribution are prefilled
- select the options "Show legend" and "Use free text"
- Altman DG (1991) Practical statistics for medical research. London: Chapman and Hall. Book info
- Cumulative frequency distribution
- Dot plot
- Box-and-whisker plot
- Format graph
- Graph legend
- Add graphical objects
- Reference lines
- Q-Q plot on Wikipedia.