non-parametric tests

non-parametric tests

An “alternative” set of statistical techniques for analysing numerical data that make no assumptions about the underlying distribution (for example, the normality of the data).
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Since language performances (TELD scores), vocabulary performances (TIFALDI scores), FAPCI scores, and auditory reasoning performances (SIMIBT scores) were not normally distributed, non-parametric tests were conducted to compare these parameters as well as to compare ordinal variables.
Non-parametric tests like Mann-Whitney were done for comparison between two groups.
The training covered concepts ranging from Introduction to SPSS and STATA; Principles of Statistical Inference; Parametric and Non-Parametric Tests; Simple and Multiple Linear Regression, ANOVA, ANCOVA, MANOVA, MANCOVA, Survival Analysis and Factor Analysis with hands-on training and practical case studies.
Biostatistics 102: quantitative data-parametric & non-parametric tests. Singapore Med J.
We extend the event study literature on the impact of IOC announcements by (i) adding additional data (through the Chinese win of the 2022 Winter Olympics bidding process), (ii) analyzing stock market effects prior to the announcements to check for leakage of the announcement, and (iii) running non-parametric tests in addition to the standard parametric tests.
As the data were discrete variables, both parametric and non-parametric tests were carried out.
The topics are descriptive statistics; probability and the foundations of inferential statistics; making inferences about one or two means; making inferences about the variability of two or more means; and making inferences about patterns, prediction, and non-parametric tests. ([umlaut] Ringgold, Inc., Portland, OR)
The distributions are not normal, hence the importance of using non-parametric tests, as regression-based results would have been less conclusive.
A note on non-parametric tests for the interaction on two-way layouts.
While using non-parametric tests, in the condition if the distribution of the cases are not even, there could be p values are calculated other than conventional p values, to reject the null hypothesis, which can ve presented a "p<0.00...
According to Gibbons (1993), non-parametric tests are considered more appropriate than classical parametric procedures for Likert-scaled data.
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