Open AccessSTATISTICAL INFERENCE AT WORK: STATISTICAL PROCESS CONTROL AS AN EXAMPLE
Author(s) -
Arthur Bakker,
Phillip Kent,
Jan Derry,
Richard Noss,
Celia Hoyles
Publication year - 2008
Publication title -
statistics education research journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.538
H-Index - 14
ISSN - 1570-1824
DOI - 10.52041/serj.v7i2.473
Subject(s) - statistical inference , inference , fiducial inference , statistical hypothesis testing , statistical process control , statistical theory , frequentist inference , computer science , statistical model , null hypothesis , process (computing) , econometrics , machine learning , statistics , artificial intelligence , mathematics , bayesian inference , bayesian probability , operating system
To characterise statistical inference in the workplace this paper compares a prototypical type of statistical inference at work, statistical process control (SPC), with a type of statistical inference that is better known in educational settings, hypothesis testing. Although there are some similarities between the reasoning structure involved in hypothesis testing and SPC that point to key characteristics of statistical inference in general, there are also crucial differences. These come to the fore when we characterise statistical inference within what we call a “space of reasons” – a conglomerate of reasons and implications, evidence and conclusions, causes and effects.
First published November 2008 at Statistics Education Research Journal: Archives