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2021/11/21 -When analysing different groups, a one-way ANOVA can tell us if there is a statistically significant difference between those groups.

Purpose: The Bonferroni correction adjusts probability (p) values because of the increased risk of a type I error when making multiple statistical tests.

The Bonferroni correction: Use α′ = α/(no. tests) as the significance level for each test. For example, with 10 groups and so 45 pairwise tests, we would use α ...

Prerequisites: This lesson assumes familiarity with multiple comparisons for follow-testing in ANOVA. You should know how to represent a statistical ...

The Bonferroni correction adjusts your significance level to control the overall probability of a Type I error for multiple hypothesis tests.

Prism uses the Bonferroni correction to do multiple comparisons following two-way ANOVA. The idea is to apply the 5% significance level to an entire family ...

The Bonferroni test, also known as "Bonferroni correction" or "Bonferroni adjustment" suggests that the p-value for each test must be equal to its alpha divided ...

This method applies to an ANOVA situation when the analyst has picked out a particular set of pairwise comparisons or contrasts or linear combinations in ...

2024/1/5 -Bonferroni test ANOVA is a test where the mean of a numerical ... The Bonferroni test ANOVA can be helpful when there are more than two groups.