Abstract—The underlying philosophy of statistical software
primarily aims to empower data analysts to concentrate on
statistical thinking and leave the computational burden to
computers. Teaching how to program statistical software,
however, is over-emphasized by some lecturers and students
may not develop the skills needed to be competent at justifying
and/or interpreting statistical results. For this reason, this
article aims to address this issue by developing a model of
teaching statistical software to strengthen secondary and
tertiary students’ capacity to understand statistical processes
and conduct statistical investigations. The model consists of six
major steps: examining data characteristics, selecting statistical
tools, understanding the strengths and weaknesses of statistical
software, checking the accuracy of statistical output,
interpreting statistical output and presenting statistical results.
Index Terms—Semantic error, statistical context, statistical
logic, statistical investigation.
Ken W. Li is with the Department of Information and Communications
Technology, Hong Kong Institute of Vocational Education (Tsing Yi), 20
Tsing Yi Road, New Territories, Hong Kong (e-mail: kenli@vtc.edu.hk).
Cite: Ken W. Li, "A Model of Teaching Statistical Computing," International Journal of Information and Education Technology vol. 6, no. 2, pp. 143-147, 2016.