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Points of significance

Analysis of variance and blocking

Nature Methods volume 11, pages 699–700 (2014)Cite this article

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Good experimental designs mitigate experimental error and the impact of factors not under study.

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Figure 1: ANOVA is used to determine significance using the ratio of variance estimates from sample means and sample values.
Figure 2: Blocking improves sensitivity by isolating variation in samples that is independent from treatment effects.
Figure 3: Application of one-factor ANOVA to comparison of three samples.
Figure 4: Including blocking isolates biological variation from the estimate of within-group variance and improves power.

References

  1. Krzywinski, M. & Altman, N. Nat. Methods 11, 597–598 (2014).

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  2. Krzywinski, M. & Altman, N. Nat. Methods 11, 215–216 (2014).

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Authors and Affiliations

  1. Martin Krzywinski is a staff scientist at Canada's Michael Smith Genome Sciences Centre.,

    Martin Krzywinski

  2. Naomi Altman is a Professor of Statistics at The Pennsylvania State University.,

    Naomi Altman

Authors
  1. Martin Krzywinski
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  2. Naomi Altman
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The authors declare no competing financial interests.

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Krzywinski, M., Altman, N. Analysis of variance and blocking. Nat Methods 11, 699–700 (2014). https://doi.org/10.1038/nmeth.3005

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