English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Received 20 March 2018 Accepted 15 May 2018 Parametric approaches in statistical analysis assume that any given data are normally distributed. Therefore, the test of whether this conventional assumption is valid should be made in this context of the available data’s normality before being passed to the application of statistical tests. The paper is focused on the normality methodologies commonly used in literature, named Kolmogorov-Smirnov, Jarque-Bera, D’agostino, Anderson Darling, Shapiro-Wilk and Ryan Joiner. In the study, the seasonal maximum data from eight streamflow gauging stations in Yesilirmak Basin was used as material. The normality in the 59% of the whole data sets were obtained as the highest result by the Kolmogorov –Smirnov approach, when compared to the other normality tests considered in the study.

Use of Non-Parametric Approaches on Normality of Hydrologic Variables