Analysis of Variance, Sign, and Wilcoxon Tests: Statistical Tests
VerifiedAdded on 2021/05/31
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Homework Assignment
AI Summary
This assignment provides an analysis of three key statistical tests: Analysis of Variance (ANOVA), Sign Test, and Wilcoxon Test. It begins by outlining the assumptions underlying the ANOVA F-test, including the random selection of samples, normal distribution of treatment populations, homogeneity of variances, and additive nature of effects. The assignment then presents a practical example involving the effect of soya protein levels on different food products, detailing the formulation of null and alternate hypotheses and the interpretation of the Fisher-F value. The document also explores the Sign test, a non-parametric test used for non-normal data, discussing its assumptions and illustrating its application with an example comparing psychology scores. Finally, it examines the Wilcoxon test, another non-parametric method used as an alternative to the t-test, particularly when data does not follow a normal distribution. The assignment covers the test's assumptions and provides an example involving the comparison of gambling playing intentions. Each test explanation includes the null and alternate hypotheses, and the interpretation of p-values. The assignment concludes with a reference to the sources used.
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