Abstract
The need for analysts with expertise in big data software is becoming more apparent in today’s society. Unfortunately, the demand for these analysts far exceeds the number available. A potential way to combat this shortage is to identify the software sought by employers and to align this with the software taught by universities. This paper will examine multiple data analysis software – Excel add-ins, SPSS, SAS, Minitab, and R – and it will outline the cost, training, statistical methods/tests/uses, and specific uses within industry for each of these software. It will further explain implications for universities and students.
DOI
10.22237/jmasm/1493599200
Recommended Citation
Ozgur, C., Dou, M., Li, Y., & Rogers, G. (2017). Selection of statistical software for data scientists and teachers. Journal of Modern Applied Statistical Methods, 16(1), 753-774. doi: 10.22237/jmasm/1493599200
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
