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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.

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