Multi-Factor Analysis of Variance

A Multi-Factor Analysis of Variance is an Analysis of Variance that is used to detect a statistic of a multi-factor model.

• Example(s)
  • Two-way ANOVA.
  • …
• Counter-Example(s):
  • One-Way ANOVA.
• See: ANOVA, Statistical Model, Response Variable, Independent Variable, Statistical Inference.

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References

2021

• (NIST, 2021) ⇒ "Multi-factor Analysis of Variance". In: NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/ 2021-01-03.
  • QUOTE: The analysis of variance (ANOVA) (Neter, Wasserman, and Kutner, 1990) is used to detect significant factors in a multi-factor model. In the multi-factor model, there is a response (dependent) variable and one or more factor (independent) variables. This is a common model in designed experiments where the experimenter sets the values for each of the factor variables and then measures the response variable.

1990

• (Neter et al., 1990) ⇒ Neter, Wasserman, and Kutner (1990), Applied Linear Statistical Models, 3rd ed., Irwin.

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