Abstract

ABSTRACT The collection of experimental leisure research data is restricted by the assumptions of positivism and empiricism. Behaviours are often measured as functions of testable stimulus factors. Organismic variables are treated statistically and experimentally as errors. The quantifiability of stimulus variables readily permits parametric analysis because the data more easily conform to the assumptions of homoscedasticity, ratio scalability, and homogeneity of variance. The dilemma burdening leisure researchers is that the majority of behavioural predictors are drawn from inherent organismic characteristics for which the experimental design framework and parametric statistical analysis are inappropriate. The leisure researcher is typically unprepared in non parametric statistical techniques, so a parametric statistical model is imposed illegitemately upon nonparametric data and consequently the violations of assumptions which occur, are ignored. Alternatively, if a nonparametric statistical analysis is imposed and the assumptions safeguarded, other researchers trained only in parametric analysis, fail to understand sufficiently, and consequently ignore the research; hence, the dilemma. This paper suggests a review of recent statistical modifications being developed, potentially providing a resolution to this dillemma.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.