# iqd

##### Industrial quality control dataset

A factory has four machines A, B, C, D. The quality control process identifies defects from each machine.

The `iqd`

dataset has four columns, one per machine; entries
correspond to the numbers of defects produced by each machine. The
`NA`

entries in a row indicate that a particular machine is
switched off.

The null hypothesis would be that there exist four non-negative numbers $p_1,p_2,p_3,p_4$ with sum 1 such that the probability of a defect arising from machine $i$ is proportional to $p_i$ if it is switched on, and zero otherwise.

It is suspected that machine D is causing some sort of interference with machine A; machine A produces very few defects when D is switched off.

The `shifts`

dataset includes only three machines, A, B, C.
There are three columns, one per machine; and three rows, one per
operator (S1, S2, S3). On S1's shift, machine C was out of
commission.

- Keywords
- datasets

##### Usage

`data(iqd)`

##### source

Data kindly supplied by Acme Corporation (widget division)

##### Examples

```
data(iqd)
aylmer.test(iqd)
aylmer.test(shifts)
```

*Documentation reproduced from package aylmer, version 1.0-1, License: GPL-2*