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The Nature Methods Points of View column column offers practical advice in design and data presentation for the busy scientist.

50+ columns of good explanations ·

With the publication of Uncertainty and the Management of Epidemics, we celebrate our 50th column! Since 2013, our Nature Methods Points of Significance has been offering crisp explanations and practical suggestions about best practices in statistical analysis and reporting. To all our readers and coauthors: thank you and see you in the next column!

Nature Methods: Points of Significance

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca

▲ Points of Significance column in Nature Methods. (Launch of Points of Significance)

≡ authors figures bibliography metrics

60 | Megahed, F.M, Chen, Y-J., Jones-Farmer, A., Rigdon, S.E., Krzywinski, M. & Altman, N. (2024) Points of significance: Comparing classifier performance with baselines. Nature Methods.

59 | Altman, N. & Krzywinski, M. (2024) Points of significance: Error in predictor variables. Nature Methods 21

58 | Derry, A., Krzywinski, M. & Altman, N. (2023) Points of significance: Convolutional neural networks. Nature Methods 20:1269–1270

57 | Derry, A., Krzywinski, M. & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20:165–167.

56 | Dey, T., Lipsitz, S.R., Cooper, Z., Trinh, Q., Krzywinski, M.& Altman, N. (2022) Points of significance: Regression modelling of time-to-event data with censoring. Nature Methods 19:1513–1515.

55 | Dey, T., Lipsitz, S.R., Cooper, Z., Trinh, Q., Krzywinski, M.& Altman, N. (2022) Points of significance: Survival analysis — time-to-event data and censoring. Nature Methods 19:906–908.

54 | Megahed, F.M, Chen, Y-J., Megahed, A., Ong, Y., Altman, N. & Krzywinski, M. (2021) Points of significance: The class imbalance problem. Nature Methods 18:1270–1272.

53 | Altman, N. & Krzywinski, M. (2021) Points of significance: Graphical assessments of tests and classifiers. Nature Methods 18:840–842

52 | Altman, N. & Krzywinski, M. (2021) Points of significance: Testing for rare conditions. Nature Methods 18:224–225.

51 | Voelkl, B., Würbel, H., Krzywinski, M. & Altman, N. (2021) Points of significance: The standardization fallacy. Nature Methods 18:5–7.

50 | Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: Uncertainty and the management of epidemics. Nature Methods 17:867–868.

49 | Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: The SEIRS model for infectious disease dynamics. Nature Methods 17:557–558.

48 | Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: Modeling infectious epidemics. Nature Methods 17:455–456.

47 | Grewal, J., Krzywinski, M. & Altman, N. (2020) Points of significance: Markov models — training and evaluation of hidden Markov models. Nature Methods 17:121–122.

46 | Grewal, J., Krzywinski, M. & Altman, N. (2019) Points of significance: Hidden Markov models. Nature Methods 16:795–796.

45 | Grewal, J., Krzywinski, M. & Altman, N. (2019) Points of significance: Markov chains. Nature Methods 16:663–664.

44 | Das, K., Krzywinski, M. & Altman, N. (2019) Points of significance: Quantile regression. Nature Methods 16:451–452.

43 | Greco, L., Luta, G., Krzywinski, M. & Altman, N. (2019) Points of significance: Analyzing outliers: Robust methods to the rescue. Nature Methods 16:275–276.

42 | Smucker, B., Krzywinski, M. & Altman, N. (2019) Points of significance: Two-level factorial experiments Nature Methods 16:211–212.

41 | Altman, N. & Krzywinski, M. (2018) Points of significance: Predicting with confidence and tolerance Nature Methods 15:843–844.

40 | Smucker, B., Krzywinski, M. & Altman, N. (2018) Points of significance: Optimal experimental design Nature Methods 15:559–560.

39 | Altman, N. & Krzywinski, M. (2018) Points of significance: Curse(s) of dimensionality Nature Methods 15:299–400.

38 | Bzdok, D., Krzywinski, M. & Altman, N. (2018) Points of significance: Statistics vs machine learning. Nature Methods 15:233–234.

37 | Bzdok, D., Krzywinski, M. & Altman, N. (2018) Points of significance: Machine learning: supervised methods. Nature Methods 15:5–6.

36 | Bzdok, D., Krzywinski, M. & Altman, N. (2017) Points of significance: Machine learning: a primer. Nature Methods 14:1119–1120.

35 | Altman, N. & Krzywinski, M. (2017) Points of significance: Ensemble methods: Bagging and random forests. Nature Methods 14:933–934.

34 | Krzywinski, M. & Altman, N. (2017) Points of significance: Classification and regression trees. Nature Methods 14:757–758.

33 | Lever, J., Krzywinski, M. & Altman, N. (2017) Points of significance: Principal component analysis. Nature Methods 14:641–642.

32 | Altman, N. & Krzywinski, M. (2017) Points of significance: Clustering. Nature Methods 14:545–546.

31 | Altman, N. & Krzywinski, M. (2017) Points of significance: Tabular data. Nature Methods 14:329–330.

30 | Altman, N. & Krzywinski, M. (2017) Points of significance: Interpreting P values. Nature Methods 14:213–214.

29 | Altman, N. & Krzywinski, M. (2017) Points of significance: P values and the search for significance. Nature Methods 14:3–4.

28 | Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Regularization. Nature Methods 13:803–804.

27 | Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Model selection and overfitting. Nature Methods 13:703–704.

26 | Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Classifier evaluation. Nature Methods 13:603–604.

25 | Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nature Methods 13:541–542.

24 | Altman, N. & Krzywinski, M. (2016) Points of significance: Regression diagnostics. Nature Methods 13:385–386.

23 | Altman, N. & Krzywinski, M. (2016) Points of significance: Analyzing outliers: Influential or nuisance. Nature Methods 13:281–282.

22 | Krzywinski, M. & Altman, N. (2015) Points of significance: Multiple linear regression. Nature Methods 12:1103–1104.

21 | Altman, N. & Krzywinski, M. (2015) Points of significance: Simple linear regression. Nature Methods 12:999–1000.

20 | Altman, N. & Krzywinski, M. (2015) Points of significance: Association, correlation and causation. Nature Methods 12:899–900.

19 | Puga, J.L, Krzywinski, M. & Altman, N. (2015) Points of significance: Bayesian networks. Nature Methods 12:799–800.

18 | Kulesa, A., Krzywinski, M., Blainey, P. & Altman, N. (2015) Points of significance: Sampling distributions and the bootstrap. Nature Methods 12:477–478.

17 | Puga, J.L, Krzywinski, M. & Altman, N. (2015) Points of significance: Bayesian statistics. Nature Methods 12:277–278.

16 | Puga, J.L, Krzywinski, M. & Altman, N. (2015) Points of significance: Bayes' theorem. Nature Methods 12:277–278.

15 | Altman, N. & Krzywinski, M. (2015) Points of significance: Split plot design. Nature Methods 12:165–166.

14 | Altman, N. & Krzywinski, M. (2015) Points of significance: Sources of variation. Nature Methods 12:5–6.

13 | Krzywinski, M., Altman, N. (2014) Points of significance: Two factor designs. Nature Methods 11:1187–1188.

12 | Krzywinski, M., Altman, N. & Blainey, P. (2014) Points of significance: Nested designs. Nature Methods 11:977–978.

11 | Blainey, P., Krzywinski, M. & Altman, N. (2014) Points of significance: Replication. Nature Methods 11:879–880.

10 | Krzywinski, M. & Altman, N. (2014) Points of significance: Analysis of variance (ANOVA) and blocking. Nature Methods 11:699–700.

9 | Krzywinski, M. & Altman, N. (2014) Points of significance: Designing comparative experiments. Nature Methods 11:597–598.

8 | Krzywinski, M. & Altman, N. (2014) Points of significance: Non-parametric tests. Nature Methods 11:467–468.

7 | Krzywinski, M. & Altman, N. (2014) Points of significance: Comparing samples — Part II — Multiple testing. Nature Methods 11:355–356.

6 | Krzywinski, M. & Altman, N. (2014) Points of significance: Comparing samples — Part I — t–tests. Nature Methods 11:215–216.

5 | Krzywinski, M. & Altman, N. (2014) Points of significance: Visualizing samples with box plots. Nature Methods 11:119–120.

4 | Krzywinski, M. & Altman, N. (2013) Points of significance: Power and sample size. Nature Methods 10:1139–1140.

3 | Krzywinski, M. & Altman, N. (2013) Points of significance: Significance, P values and t–tests. Nature Methods 10:1041–1042.

2 | Krzywinski, M. & Altman, N. (2013) Points of significance: Error bars. Nature Methods 10:921–922.

1 | Krzywinski, M. & Altman, N. (2013) Points of significance: Importance of being uncertain. Nature Methods 10:809–810.

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Comparing classifier performance with baselines

Sat 23-03-2024

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This month, we will illustrate the importance of establishing a baseline performance level.

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▲ Nature Methods Points of Significance column: Comparing classifier performance with baselines. (read)

Unfortunately, baselines are often overlooked and, in the presence of a class imbalance5, must be established with care.

Megahed, F.M, Chen, Y-J., Jones-Farmer, A., Rigdon, S.E., Krzywinski, M. & Altman, N. (2024) Points of significance: Comparing classifier performance with baselines. Nat. Methods 20.

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How Analyzing Cosmic Nothing Might Explain Everything

Thu 18-01-2024

Huge empty areas of the universe called voids could help solve the greatest mysteries in the cosmos.

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▲ How Analyzing Cosmic Nothing Might Explain Everything. Text by Michael Lemonick (editor), art direction by Jen Christiansen (Senior Graphics Editor), source: SDSS

The graphic uses the latest data from SDSS 12 and is an update to my Superclusters and Voids poster.

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Shown here are voids discovered by the Sloan Digital Sky Survey (SDSS), along with a selection of 16 previously named voids. Scientists expect voids to be evenly distributed throughout space—the lack of voids in some regions on the globe simply reﬂects SDSS’s sky coverage.”

voids

Sofia Contarini, Alice Pisani, Nico Hamaus, Federico Marulli Lauro Moscardini & Marco Baldi (2023) Cosmological Constraints from the BOSS DR12 Void Size Function Astrophysical Journal 953:46.

Nico Hamaus, Alice Pisani, Jin-Ah Choi, Guilhem Lavaux, Benjamin D. Wandelt & Jochen Weller (2020) Journal of Cosmology and Astroparticle Physics 2020:023.

Sloan Digital Sky Survey Data Release 12

constellation figures

Alan MacRobert (Sky & Telescope), Paulina Rowicka/Martin Krzywinski (revisions & Microscopium)

stars

Hoffleit & Warren Jr. (1991) The Bright Star Catalog, 5th Revised Edition (Preliminary Version).

cosmology

H₀ = 67.4 km/(Mpc·s), Ω_m = 0.315, Ω_v = 0.685. Planck collaboration Planck 2018 results. VI. Cosmological parameters (2018).