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  - added §10.3.2 with R `curve( dnorm(), ...)`
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126 changes: 64 additions & 62 deletions QMS-EN.log
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\TU/lmr/m/sl/10 10.4. DOES MY VARIABLE HAVE A NORMAL PROBABILITY DISTRIBUTION?
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Chapter 11.
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Chapter 11.
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[]\TU/lmr/m/n/10 Choose \TU/lmtt/m/n/10 Pearsons \TU/lmr/m/n/10 correlation coe
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[]\TU/lmtt/m/n/10 ## Number of categories should be increased in order to coun
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Appendix C.
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(\#eq:prob-standardnormal)
\end{equation}

### R

The normal probability distribution in Figure \@ref(fig:normalprobabilitydistribution) may be plotted in R using the command below. A `curve` is plotted, with `x` in the specified domain, and `y` being the function which computes the normal probability density using equation \@ref(eq:prob-normal):
```{r curve.dnorm}
curve( dnorm( x, mean=0, sd=1 ), # function specifying y values, normal density
from=-5, to=+5, # domain of x
lwd=4, # line width is 4x default value
xlab="x", ylab="P(x)" # labels along x and y axes
)
```

If used with the additional argument `curve( ..., add=TRUE )`, then the curve will be added to the most recent plot (see e.g. Figure \@ref(fig:itunesmeanshist) below).

## Does my variable have a normal probability distribution? {#sec:isvarnormaldistributed}

```{r itunestimeshist-prep, echo=FALSE}
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