`library(bcc)`

`qcc`

is a package for **statistical process control and control charts** built based on the `qcc`

package, with new functions allowing the use of beta control charts.

This package allows the user to:

- build beta control charts

As the package uses the `qcc`

package as the basis for building the graphics, all `qcc`

functions and utilities also work on `bcc`

. For more informations please consider visiting https://luca-scr.github.io/qcc/.

You can use `bcc`

in two basic ways:

discrete data representing the sample size using

`type = 1`

;continuous data without sample size with values in the range between [0.1] using

`type = 2`

; you can make a ratio between the data to be analyzed for example.

```
data("Montgomery2005")
bcc(data=Montgomery2005$Defective, sizes = Montgomery2005$Sample, type=1)
```

```
data("Drapper1998data")
bcc(data = Drapper1998data, type = "2")
```

```
#> List of 11
#> $ call : language qcc(data = data, type = "beta.p", center = center, std.dev = std.dev, limits = limits, data.name = data.name| __truncated__ ...
#> $ type : chr "beta.p"
#> $ data.name : chr "data"
#> $ data : num [1:34, 1] 1 1 1 0.998 1 ...
#> ..- attr(*, "dimnames")=List of 2
#> $ statistics : Named num [1:34] 1 1 1 0.998 1 ...
#> ..- attr(*, "names")= chr [1:34] "1" "2" "3" "4" ...
#> $ sizes : int [1:34] 1 1 1 1 1 1 1 1 1 1 ...
#> $ center : num 0.999
#> $ std.dev : num 0.000936
#> $ confidence.level: num 0.9
#> $ limits : num [1, 1:2] 0.994 1
#> ..- attr(*, "dimnames")=List of 2
#> $ violations :List of 2
#> - attr(*, "class")= chr "qcc"
```

Montgomery, D.C. (2009) *Introduction to Statistical Quality Control*, 6th ed. New York: John Wiley & Sons.

Scrucca, L. (2004) qcc: an R package for quality control charting and statistical process control. *R News* 4/1, 11-17.

SANT’ANNA, Ângelo M. O; CATEN, Carla Schwengber ten. *Beta control charts forsave monitoring fraction data.* Expert Systems With Applications, p. 10236-10243. 1 set. 2012.