plotBinconf | R Documentation |

Function outputting a plot of confidence interval around a proportion for a range of sample sizes

```
plotBinconf(proportion, minN, maxN, step = 1, conf = 0.95, fixYlim = FALSE)
plotCIProportion(
proportion,
minN,
maxN,
step = 1,
conf = 0.95,
fixYlim = FALSE
)
```

`proportion` |
numeric: the proportion sought (actual proportion will be nearest possible for each n) |

`minN` |
numeric: the smallest sample size, n, to estimate and plot |

`maxN` |
numeric: the largest n |

`step` |
numeric: the steps to use between minN and maxN, defaults to 1 but set higher if plotting a wide range of n |

`conf` |
numeric: confidence interval width, usually .95 |

`fixYlim` |
logical: if FALSE, ggplot finds sensible y limits, if TRUE, y axis runs from 0 to 1 |

a ggplot object, by default that will print but you can save it and modify it as you like

This little function just plots confidence intervals (CIs) for a proportion for a range of sample sizes. I wrote
it after writing `classifyScoresVectorByRCI`

which will give CIs around observed proportions and
I thought that for people not entirely familiar with and comfortable with CIs it might be useful for them to be
able to see a plot of how intervals around observed proportions change with sample size.
#'

Started before 5.iv.21

Chris Evans

Other confidence interval functions:
`getCIPearson()`

,
`getCISpearman()`

,
`plotCIPearson()`

Other demonstration functions:
`plotCIPearson()`

```
## Not run:
### 95% CI around proportion .5 for n from 10 to 70
plotBinconf(.5, 10, 70, conf = .95) # don't have to declare conf, defaults to .95
### notice that the observed proportion wiggles up and down as n increases as
### you can only have integer counts so functions gets nearest to the desired
### proportion, here .5, possible for that n, so for n = 10, we can have perfect .5
### but for n = 11 6/11 is .545454..
### 90% CI around proportion .5 for n from 10 to 70
plotBinconf(.5, 10, 70, conf = .90)
### 90% CI around proportion .5 for n from 100 to 200
plotBinconf(.5, 10, 70, conf = .90)
### same but fixing y limits to 0 and 1
plotBinconf(.5, 10, 70, conf = .90, fixYlim = TRUE)
### default 95% CI, exporting to tmpPlot and then changing plot
plotBinconf(.5, 10, 70) -> tmpPlot
tmpPlot +
ggtitle("95% CI around proportion .5 for n from 10 to 70") +
theme_bw()
### other inputs
plotBinconf(0, .95, 10, 70)
plotBinconf(1, .95, 10, 70)
plotBinconf(.7, .95, 100, 200)
plotBinconf(.3, .95, 100, 700, 5)
## End(Not run)
```

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