Multiple comparisons

Multiple Comparisons

Multiple comparisons (pronunciation: /ˈmʌltɪpəl kəmˈparɪsənz/) is a term used in statistics to describe situations where one considers a set of statistical inferences simultaneously.

Etymology

The term "multiple comparisons" originates from the field of statistical analysis, where it refers to the process of comparing multiple (or "multiple") observations or groups to understand their differences or similarities.

Definition

In the context of statistical hypothesis testing, a multiple comparison procedure is an area of statistics that involves the simultaneous testing of several different hypotheses. The goal of these procedures is to identify which of the tested hypotheses are different from the others, while controlling the Type I error rate.

Related Terms

• Familywise error rate: This is the probability of making one or more false discoveries, or Type I errors when performing multiple hypotheses tests.

• Bonferroni correction: A method used to counteract the problem of multiple comparisons. It is named after Italian mathematician Carlo Emilio Bonferroni.

• False discovery rate: This is a method used in multiple hypothesis testing to correct for multiple comparisons.

• Post-hoc analysis: This is any statistical analysis that was not specified before the data was collected, often used in the context of multiple comparisons.

• Tukey's range test: A single-step multiple comparison procedure and statistical test. It can be used to find means that are significantly different from each other.

See Also

• Statistical significance
• Type I and type II errors
• Statistical hypothesis testing
• Analysis of variance

External links

• Medical encyclopedia article on Multiple comparisons
• Wikipedia's article - Multiple comparisons

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