Literaturnachweis - Detailanzeige
| Autor/inn/en | Holman, Justin O.; Hacherl, Allie |
|---|---|
| Titel | Teaching Monte Carlo Simulation with Python |
| Quelle | In: Journal of Statistics and Data Science Education, 31 (2023) 1, S.33-44 (12 Seiten)
PDF als Volltext |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| DOI | 10.1080/26939169.2022.2111008 |
| Schlagwörter | Teaching Methods; Monte Carlo Methods; Programming Languages; Statistics Education; Decision Making; Computer Science Education; Computer Software; Undergraduate Students; Spreadsheets; Business Schools; Business Administration Education; Course Descriptions; Advanced Courses |
| Abstract | It has become increasingly important for future business professionals to understand statistical computing methods as data science has gained widespread use in contemporary organizational decision processes in recent years. Used by scores of academics and practitioners in a variety of fields, Monte Carlo simulation is one of the most broadly applicable statistical computing methods. This article describes efforts to teach Monte Carlo simulation using Python. A series of simulation assignments are completed first in Google Sheets, as described in a previous article. Then, the same simulation assignments are completed in Python, as detailed in this article. This pedagogical strategy appears to support student learning for those who are unfamiliar with statistical computing but familiar with the use of spreadsheets. Supplementary materials for this article are available online. (As Provided). |
| Anmerkungen | Taylor & Francis. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2024/1/01 |
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