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Parametric and Non-Parametric Tests

Parametric and Non Parametric tests

In statistics, a difference is made between parametric and non-parametric tests. You need to know exactly what these mean particularly as you are writing your research proposal. Data analysis route when executing project data analysis requires choosing a test that is consistent with the research hypotheses. The examples of parametric tests include paired t-test, unpaired t-test, person correlation, and One Way ANOVA. Non-parametric tests include Kruskal Wallis test, Spearman Correlation, Wilcoxon Rank sum test, and Mann-Whitney U test. There are conditions that determine when to do parametric or non-parametric tests. At Tobit Research Consulting Limited, clarity is made between the two in relation to data analysis and data entry. When wring a research proposal, you will be guided on how to carefully evaluate your variables to ensure that the tests are relevant and suitable to your study.

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