Jock MacKay

Adjunct Professor

Jock MacKayContact Information:
Jock MacKay

​Research interests

My research interests span a variety of areas in the application of statistical methods to the improvement of manufacturing processes, including experimental design and observational methods. In collaboration with my colleague Stefan Steiner, we have developed these methods into a system for reducing variation in process outputs. This work led to our book, Statistical Engineering.

Over the past few years, manufacturing organizations have realized the cost and competitive advantage of reducing variation in process outputs. Statistical methods and systems employing such methods, for example Six Sigma, have become increasingly popular. It is therefore of interest to construct systems and especially strategies that can be applied broadly and effectively. Hoerl and Snee use the term “Statistical Engineering” to describe these efforts.

Recently, Stefan and I, together with our graduate students, have concentrated on the assessment of industrial and medical measurement systems. This area of research has proved very fruitful with a number of publications and many further opportunities.

A second area of interest arises through collaboration with a team of ornithologists who are studying the effects of changing environmental conditions on the choice of nest location and nesting success for wood thrushes, a lovely neo-tropical migrant relatively common in the Region of Waterloo. I help with the study design and analysis of the collected data.


Over the past 30 years, I have consulted with a large number of manufacturing organizations, especially in the automotive sector, including General Motors, Ford, Toyota, Wescast Industries, Imperial Oil, Northern Telecom, Campbell Soup, Fisher and Paykel and more recently Research in Motion (RIM), the makers of Blackberry.

Together with Stefan Steiner, we were awarded the Wilcoxin prize for the best applied paper in the journal Technometrics in 2004. The article, entitled "Scale Counting," provides methods for using weighing to efficiently count large numbers of small items. In 2011, Ryan Browne (one of our recent PhD graduates), Stefan and I were awarded the W.J. Youden Award in Interlaboratory Testing for our paper “Leveraged Gauge R&R Studies” in Technometrics.

In writing our book on Statistical Engineering, I found many glaring holes in my understanding of how Statistics works, or to put it more optimistically, a plethora of new problems to work on. Some current examples are:

  • the assessment of binary measurement systems
  • the design of baseline studies to provide maximal information in the sequential search for a dominant cause of variation
  • the foundations of SPC
  • models and study plans for measurement system studies when the distribution of the true values is not normal.

Selected publications


Steiner S.H. and MacKay, R.J. (2005). Statistical Engineering. Quality Press, Milwaukee, USA

Papers in refereed journals

  • Steiner SH and Mackay, RJ (2012) Invited panellists for “Statistical Engineering- Forming the Foundations” ed. Anderson CM and Lu L, Quality Engineering, 24, 110-134.
  • Steiner SH, Stevens NT, Browne RP, and MacKay RJ (2011). “Planning and analysis of measurement reliability studies”, Canadian Journal of Statistics, 39, 344-355.
  • Nathaniel T. Stevens, Stefan H. Steiner, R. Jock MacKay and Ian Smith (2011),” Monitoring radiation use in cardiac fluoroscopy imaging procedures”, Med. Phys. 38, 317-326.
  • Stevens N, Browne R, Steiner SH and MacKay RJ (2010) “Augmented Measurement System Assessment,” Journal of Quality Technology, 42, 388-399.
  • Browne R, Steiner SH, MacKay RJ (2010) “Leveraged Gauge R&R Studies,” Technometrics, 52, 294-302.
  • Danila O, Steiner SH and MacKay RJ (2010), “Assessment of a Binary Measurement System in Current Use,” Journal of Quality Technology, 42, 152-164.
  • Browne R, Steiner SH, MacKay RJ (2010) “Optimal Two-Stage Reliability Studies,”Statistics in Medicine, 29, 229-235.
University of Waterloo
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