Large sample size, significance level, and the effect size: Solutions to perils of using big data for academic research
Jalayer Khalilzadeh and
Asli D.A. Tasci
Tourism Management, 2017, vol. 62, issue C, 89-96
Abstract:
The increasing availability of and attention to big data accumulated on different aspects of demand and supply side of industries has resulted in utilization of large samples for academic publications as well. Using large samples, however, creates the issue of guaranteed statistical significance and thus demands reporting the practical significance by using effect size measures. This manuscript is a guide to inform tourism and hospitality academia of the effect size measures for the most commonly used statistical tests.
Keywords: Big data; Large sample; Statistical significance; Practical significance; Effect size (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S026151771730078X
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:touman:v:62:y:2017:i:c:p:89-96
DOI: 10.1016/j.tourman.2017.03.026
Access Statistics for this article
Tourism Management is currently edited by Chris Ryan
More articles in Tourism Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().