# qqnorm

##### Quantile-Quantile Plots

`qqnorm`

is a generic function the default method of which
produces a normal QQ plot of the values in `y`

.
`qqline`

adds a line to a “theoretical”, by default
normal, quantile-quantile plot which passes through the `probs`

quantiles, by default the first and third quartiles. `qqplot`

produces a QQ plot of two datasets. Graphical parameters may be given as arguments to `qqnorm`

,
`qqplot`

and `qqline`

.

- Keywords
- hplot, distribution

##### Usage

```
qqnorm(y, …)
# S3 method for default
qqnorm(y, ylim, main = "Normal Q-Q Plot",
xlab = "Theoretical Quantiles", ylab = "Sample Quantiles",
plot.it = TRUE, datax = FALSE, …)
```qqline(y, datax = FALSE, distribution = qnorm,
probs = c(0.25, 0.75), qtype = 7, …)

qqplot(x, y, plot.it = TRUE, xlab = deparse(substitute(x)),
ylab = deparse(substitute(y)), …)

##### Arguments

- x
- The first sample for
`qqplot`

. - y
- The second or only data sample.
- xlab, ylab, main
- plot labels. The
`xlab`

and`ylab`

refer to the y and x axes respectively if`datax = TRUE`

. - plot.it
- logical. Should the result be plotted?
- datax
- logical. Should data values be on the x-axis?
- distribution
- quantile function for reference theoretical distribution.
- probs
- numeric vector of length two, representing probabilities. Corresponding quantile pairs define the line drawn.
- qtype
- the
`type`

of quantile computation used in`quantile`

. - ylim, …
- graphical parameters.

##### Value

For `qqnorm`

and `qqplot`

, a list with components

`y`

vector, i.e., the corresponding y
coordinates *including*.

`NA`

s##### References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988)
*The New S Language*.
Wadsworth & Brooks/Cole.

##### See Also

`ppoints`

, used by `qqnorm`

to generate
approximations to expected order statistics for a normal distribution.

##### Examples

`library(stats)`

```
require(graphics)
y <- rt(200, df = 5)
qqnorm(y); qqline(y, col = 2)
qqplot(y, rt(300, df = 5))
qqnorm(precip, ylab = "Precipitation [in/yr] for 70 US cities")
## "QQ-Chisquare" : --------------------------
y <- rchisq(500, df = 3)
## Q-Q plot for Chi^2 data against true theoretical distribution:
qqplot(qchisq(ppoints(500), df = 3), y,
main = expression("Q-Q plot for" ~~ {chi^2}[nu == 3]))
qqline(y, distribution = function(p) qchisq(p, df = 3),
prob = c(0.1, 0.6), col = 2)
mtext("qqline(*, dist = qchisq(., df=3), prob = c(0.1, 0.6))")
```

*Documentation reproduced from package stats, version 3.3.3, License: Part of R 3.3.3*