iqd: Industrial quality control dataset

In aylmer: A generalization of Fisher's exact test

Description

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.

Usage

data(iqd)

Source

Data kindly supplied by Acme Corporation (widget division)

Examples

data(iqd)

aylmer.test(iqd)
aylmer.test(shifts)

aylmer documentation built on May 29, 2017, 1:12 p.m.