Large sample size, significance level, and the effect size: Solutions to perils of using big data for academic research
J Khalilzadeh, ADA Tasci�- Tourism Management, 2017 - Elsevier
Tourism Management, 2017•Elsevier
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.
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.
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.
Elsevier