This is a session of Topic 4: Statistics education/training and the workplace Full topic list
(Thursday 6th, 10:30-12:30)
Statistics education and the engineering world
AbstractAlthough there is general awareness of the importance of statistics across engineering, considerations of the how, what and when are fragmented. Possibly one reason for this is that statistical needs in engineering are substantial but not readily categorised. Statistical literacy is needed for engineers to interact with a range of co-workers across workplaces, but a wide variety of statistical methods and methodologies are also used across engineering, some of which are sophisticated conceptually or mathematically or both. As well, statistical thinking is needed alongside mathematical thinking in many real and multi-faceted engineering problems. Statistics has often seemed to take a “backseat” in engineering education, particularly with engineering students, but, as indicated by the US Engineering Criteria 2000, the importance of statistics in engineering needs greater prominence. Because of the range and unpredictability of engineering statistical needs, engineering students in undergraduate programs need an introduction to statistical thinking, concepts and techniques that they can use immediately in real contexts, and a coherent and logical development that optimises understanding as well as providing a basis for ongoing learning. This diversity of statistical needs in workplaces is paralleled by an increasing presence of statistical challenges in engineering research, ranging from environmental and sustainability issues, to signal processing and communications, to medical engineering, to management and industrial processes, to traffic.
Statistical education in the engineering workplace requires considerations of the workers past and futures - their individual and collective backgrounds, and clear identification of the purpose of the workplace education. Thus Statistics Education for, and in, the Engineering World is a broad and rich topic involving consideration of sound foundations for a large variety of workplaces, projects and responsibilities. Courses need to facilitate sound statistical perception to enable students to continue developing statistical thinking within their own contexts, from the most practical to the most theoretical.
There are also other intriguing aspects on the interface of statistics and engineering. The statistics profession is facing similar challenges to the engineering profession, albeit with smaller numbers, of producing multi-skilled but deeply educated graduates who can cope with technological, management, communication and deep problem-solving issues. Accreditation models reflect similarities across the range of workplaces and work needs of the two professions. There are exciting possibilities for the interface of statistics and engineering in education to reflect their many interfaces in the workplace as well as research and development, and for the two professions to support each other in all educational aspects: undergraduate, postgraduate, research, workplace and professional.