Choosing Among Computational Software Tools to Enhance Learning in Introductory Business Statistics

Marina E. Johnson; Mark L. Berenson

doi:10.1111/dsji.12186

Choosing Among Computational Software Tools to Enhance Learning in Introductory Business Statistics

Marina E. Johnson, Mark L. Berenson

Information Management and Business Analytics

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

AACSB has now mandated that analytics be integrated into the undergraduate business curriculum. Given that the subject of statistics provides the underpinnings of the developing discipline of business analytics, this article focuses on effective course delivery aimed at enhancing the learning of introductory business statistics in the modern world of big data. To this end, the choice and use of computational software tools are essential to the successful delivery of the course. A set of seven competing tools are compared and contrasted, their advantages and disadvantages are discussed, and a link is provided to show demonstrations of needed instructions and resulting output.

Original language	English
Pages (from-to)	214-238
Number of pages	25
Journal	Decision Sciences Journal of Innovative Education
Volume	17
Issue number	3
DOIs	https://doi.org/10.1111/dsji.12186
State	Published - 2019

Keywords

Business Statistics
Computational Software Tools
and GAISE College Report

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10.1111/dsji.12186

Cite this

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Choosing Among Computational Software Tools to Enhance Learning in Introductory Business Statistics

Abstract

Keywords

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