Note: This page has been translated by MathWorks. Please click here

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

Normal probability plot

`normplot(x)`

`h = normplot(x)`

`normplot(`

displays a normal probability plot of
the data contained in `x`

)`x`

. Use a normal probability plot to
assess visually whether the sample data in `x`

comes from a
population with a normal distribution. If the sample data has a normal distribution,
then the data appears along the reference line. Distributions other than normal can
introduce curvature in the plot.

`normplot`

matches the quantiles of sample data to the quantiles of
a normal distribution. The sample data is sorted and plotted on the x-axis. The y-axis
represents the quantiles of the normal distribution, converted into probability values.
Therefore, the y-axis scaling is not linear.

Where the x-axis value is the *i*th sorted value from a sample of
size *N*, the y-axis value is the midpoint between evaluation points of
the empirical cumulative distribution function of the data. In the case of uncensored
data, the midpoint is equal to $$\frac{\left(i-0.5\right)}{N}$$. When the data includes censored observations, use `probplot`

instead.

`normplot`

superimposes a reference line to assess the linearity of
the plot. The line goes through the first and third quartiles of the data.

Was this topic helpful?