Assumption for 1 sample T test: Data are normally distributed. We have discussed in the last article on how to check the normality assumption of a quantitative data. One issue being highlighted was that these formal normality tests are very sensitive to the sample size of the variable concerned. As seen here, table II shows that the normality assumptions for both the systolic and diastolic bloo...

Although non-parametric tests have already been proposed for that purpose, statistical significance tests for non-standard measures (different from the classification error) are less often used in the literature. This paper is an attempt at empirically verifying how these tests compare with more classical tests, on various conditions. More precisely, using a very large dataset to estimate the w...

evaluation of river discharges trends is very important for water resources management and design of irrigation and drainage networks. in this research, annual, seasonal and monthly trends of maroon river discharge were evaluated using the mann-kendall and sen’s slope estimator non-parametric tests and the regression analysis parametric test. for this purpose, river discharge data from five h...

the objective of this study was to compare non-parametric stability procedures, and to apply different non-parametric tests for genotype × environment interaction (g×e) on seed yield data of 17 chickpea genotypes grown during 2004-05 growing seasons in 10 rainfed environments in iran. the non-parametric measures used for g × e interaction were highly significant (p