Visions of Type
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If you live in a city, birds are essentially the only wildlife that you meet during your day.
Depending on where you live, you might come several species without even trying. In Vancouver, on a 10 minute walk around my house, I have a good chance to see rock doves (pigeons), crows, mallars, wigeons, hooded mergansers (if I'm lucky), common starlings, house sparrows (sigh), house finches, song sparrows, red-winged black birds, white-crowned sparrows, bushtits, black-capped chickadees, northern flickers, great blue herons, and the mother-of-all-honkers: Canada geese.
Birds and letters are everywhere—art of nature and man.
Letter forms, on the other hand, are the art that is also everywhere. Every typeface is an artistic expression.
Regardless where you live, sadly, you are likely to come across mutants like Comic Sans, Arial and Times New Roman — odious creatures from the shallows. Try to find Gotham, Gill Sans, Frutiger, or Garamond.
Bird songs can be visualized with a spectrogram — a visualization of the frequency components (vertical axis) in the call as a function of time (horizontal axis).
For example, below is a crop of a recording of the American goldfinch, who eats a potato chip in about 0.5 seconds. And when in flight, he has it with dip.
The full recording from the Cornell Lab Macaulay Library is shown below.
Spectrograms give us detailed insight into the fine structure of a vocalization. For example, the black-capped chicadee's “fee-bee” (or cheeseburger) actually has a very short pause (about 50 ms) in the “bee”, making it more of a “be-e”. Below is a recording of this call.
One of my favourite bird sounds is the “sawing machine” of the marsh wren. They often hide in tall reeds around ponds and lakes, making them hard to spot — by eye, but not by ear!
Mnemonics of bird songs help you remember the call and recognize the bird. It's so much easier to think "Quick, three beers!" — the call of the Olive-sided flycatcher — rather than "Chirp, chirp, chirp."
The mnemonic captures the cadence and repetition scheme of the song. For example, if you listen to the white-throated sparrow you can't help but think that this little guy is trying to tell us something.
French Zonotrichia albicollis: Baisse ta jupe, Philomène, Philomène, Philomène. How differently we hear!
—Madelaine Lemieux (via Twitter)
Potato chip!
American Goldfinch (Spinus tristis)
Here here. Come right here, dear.
Baltimore Oriole (Icterus galbula)
Who cooks for you?
Barred Owl (Strix varia)
Here sweetie.
Black-capped Chickadee (Poecile atricapillus)
Trees, trees, murmuring trees.
Black-throated Green Warbler (Setophaga virens)
Drink your tea.
Eastern Towhee (Pipilo erythrophthalmus)
Are you awake? Me too.
Great Horned Owl (Bubo virginianus)
Qu'est-ce qu-il dit?
Great Kiskadee (Pitangus sulphuratus)
Fire fire. Where where? Here here! See it, see it.
Indigo Bunting (Passerina cyanea)
Clear. Wick, wick, wick.
Northern Flicker (Colaptes auratus)
Quick, three beers!
Olive-sided Flycatcher (Contopus cooperi)
Where are you? Here I am.
Red-eyed Vireo (Vireo olivaceus)
Chubby chubby cheeks. Chubby cheeks.
Ruby-crowned Kinglet (Regulus calendula)
See me, pretty, pretty me.
White-crowned Sparrow (Zonotrichia leucophrys)
Dear sweet Canada Canada Canada.
White-throated Sparrow (Zonotrichia albicollis)
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If you love birds and typography, these posters are for you. The mnemonic for the bird's song is presented on a background that proportionally presents the bird's plumage colors.
Some posters create natural sets.
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And if you explore the posters, you just might find the bird too.
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Happy 2025 π Day—
TTCAGT: a sequence of digits
Celebrate π Day (March 14th) and sequence digits like its 1999. Let's call some peaks.
Crafting 10 Years of Statistics Explanations: Points of Significance
I don’t have good luck in the match points. —Rafael Nadal, Spanish tennis player
Points of Significance is an ongoing series of short articles about statistics in Nature Methods that started in 2013. Its aim is to provide clear explanations of essential concepts in statistics for a nonspecialist audience. The articles favor heuristic explanations and make extensive use of simulated examples and graphical explanations, while maintaining mathematical rigor.
Topics range from basic, but often misunderstood, such as uncertainty and P-values, to relatively advanced, but often neglected, such as the error-in-variables problem and the curse of dimensionality. More recent articles have focused on timely topics such as modeling of epidemics, machine learning, and neural networks.
In this article, we discuss the evolution of topics and details behind some of the story arcs, our approach to crafting statistical explanations and narratives, and our use of figures and numerical simulations as props for building understanding.
Altman, N. & Krzywinski, M. (2025) Crafting 10 Years of Statistics Explanations: Points of Significance. Annual Review of Statistics and Its Application 12:69–87.
Propensity score matching
I don’t have good luck in the match points. —Rafael Nadal, Spanish tennis player
In many experimental designs, we need to keep in mind the possibility of confounding variables, which may give rise to bias in the estimate of the treatment effect.
If the control and experimental groups aren't matched (or, roughly, similar enough), this bias can arise.
Sometimes this can be dealt with by randomizing, which on average can balance this effect out. When randomization is not possible, propensity score matching is an excellent strategy to match control and experimental groups.
Kurz, C.F., Krzywinski, M. & Altman, N. (2024) Points of significance: Propensity score matching. Nat. Methods 21:1770–1772.
Understanding p-values and significance
P-values combined with estimates of effect size are used to assess the importance of experimental results. However, their interpretation can be invalidated by selection bias when testing multiple hypotheses, fitting multiple models or even informally selecting results that seem interesting after observing the data.
We offer an introduction to principled uses of p-values (targeted at the non-specialist) and identify questionable practices to be avoided.
Altman, N. & Krzywinski, M. (2024) Understanding p-values and significance. Laboratory Animals 58:443–446.
Depicting variability and uncertainty using intervals and error bars
Variability is inherent in most biological systems due to differences among members of the population. Two types of variation are commonly observed in studies: differences among samples and the “error” in estimating a population parameter (e.g. mean) from a sample. While these concepts are fundamentally very different, the associated variation is often expressed using similar notation—an interval that represents a range of values with a lower and upper bound.
In this article we discuss how common intervals are used (and misused).
Altman, N. & Krzywinski, M. (2024) Depicting variability and uncertainty using intervals and error bars. Laboratory Animals 58:453–456.