Transcription of Volume 15, Number 12, October, 2010 ISSN 1531 …
{{id}} {{{paragraph}}}
Example: tourism industry
Volume 15, Number 12, October, 2010 ISSN 1531 …
A peer-reviewed electronic journal. Copyright is retained by the first or sole author, who grants right of first publication to the Practical Assessment, Research & Evaluation. Permission is granted to distribute this article for nonprofit, educational purposes if it is copied in its entirety and the journal is credited. Volume 15, Number 12, October, 2010 ISSN 1531-7714 Improving your data transformations: Applying the Box-Cox transformation Jason W. Osborne, North Carolina State University Many of us in the social sciences deal with data that do not conform to assumptions of normality and/or homoscedasticity/homogeneity of variance. Some research has shown that parametric tests ( , multiple regression, ANOVA) can be robust to modest violations of these assumptions. Yet the reality is that almost all analyses (even nonparametric tests) benefit from improved the normality of variables, particularly where substantial non-normality is present.
Practical Assessment, Research & Evaluation, Vol 15, No 12 Page 3 Osborne, Applying Box-Cox data that are counts of occurrences, such as number of times a student was suspended in a given year or the
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: