2017
DOI: 10.1016/j.tourman.2017.03.026
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Large sample size, significance level, and the effect size: Solutions to perils of using big data for academic research

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Cited by 199 publications
(111 citation statements)
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“…Once the ideal cluster solution was determined according to the criteria set out by Hair et al [ 58 ], the profiles of the different groups were determined, using all those variables not included in the cluster analysis. Chi-square tests, calculating the value of the Contingency Coefficient (C 2 ) to verify the size effect and the intensity of the association between the qualitative variables compared the results through the performance of the ANOVA test for the continuous variables and for the qualitative variables [ 61 ]. The significance level was established at a value of p ≤ 0.05.…”
Section: Methodsmentioning
confidence: 99%
“…Once the ideal cluster solution was determined according to the criteria set out by Hair et al [ 58 ], the profiles of the different groups were determined, using all those variables not included in the cluster analysis. Chi-square tests, calculating the value of the Contingency Coefficient (C 2 ) to verify the size effect and the intensity of the association between the qualitative variables compared the results through the performance of the ANOVA test for the continuous variables and for the qualitative variables [ 61 ]. The significance level was established at a value of p ≤ 0.05.…”
Section: Methodsmentioning
confidence: 99%
“…Differences in the adjusted days of MVPA between disability groups and with no disabilities were tested. A conversion of standard deviation of the adjusted mean number of days was used by the 95% confidence intervals to then be used to measure effect sizes from Cohen’s d. Measurement of effect sizes through differences of means were used to determine the practical significance in addition to the p -values given from the statistical significance [40]. Interpretations of these effect sizes were based on Cohen’s d interpretation that values between 0.20–0.49 were small, 0.50–0.79 were medium and over 0.80 were large [41].…”
Section: Methodsmentioning
confidence: 99%
“…However, this statistical test is used to interpret what local communities view on conservation, and this is not just to accept or reject null hypothesis (Peeters 2016). In addition, sample size is also relatively large (Khalilzadeh and Tasci 2017). In this study, a p-value greater than 0.05 but less than 0.1 is considered important or has some significant influence on conservation supports by local communities.…”
Section: Discussionmentioning
confidence: 97%