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Steve Dodge

@jsdodge.fediscience.org.ap.brid.gy

Physics professor @ Simon Fraser University. Experimental research in quantum materials and optical spectroscopy. [bridged from https://fediscience.org/@jsdodge on the fediverse by https://fed.brid.gy/ ]

198 Posts58 Follower6 Folgt
David Ho@davidho.bsky.social · 5d ago

@kimberlynicholas.bsky.social is a Professor of Sustainability Science at Lund University. She researches climate action, sustainable farming, and land use. She is the author of the bestselling book Under the Sky We Make and the newsletter We Can Fix It. She also hosts the podcast Climate Actually.

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Erik Angner@erikangner.com · last wk.

The Prime Minister of Sweden 🇸🇪 Ulf Kristersson just dismissed my colleague Åsa Wikforss – Professor of Theoretical Philosophy at Stockholm University, Member of the Swedish Academy and the Royal Academy of the Sciences, and celebrated author of numerous books – as "princess" 🧵

John D. Cook@johndcook.mathstodon.xyz.ap.brid.gy · 3mo ago

The distinction between variables from parameters is often presented poorly. Here's how to present it well. https://www.johndcook.com/blog/2026/06/30/variables-and-parameters/

Distinguishing variables from parameters

Imagine the following dialog. **Professor** : _f_ is a function of a real variable _x_ that takes a real parameter _k_. **Student** : What’s a parameter? **Professor** : It’s a constant that can vary. **Student** : Then if it can vary, isn’t it a variable? **Professor** : Sorta, but no not really. This conversation plays out over and over, and unfortunately it often ends as it does above, with the student confused. Here’s how I believe the conversation should continue. **Professor** : You’re absolutely right that _f_ is a function of two variables, _x_ and _k_. But usually _k_ is fixed in the context of a specific application and _x_ is not. A different application might have a different, but also fixed, value of _k_. So it is helpful to think of _f_(_x_ ; _k_), a function of _x_ with a parameter _k_ , rather than _f_(_x_ , _k_), a function of two variables. The former carries more information, giving a hint as to how the numbers are used. Is there really a difference between a parameter and a variable? In a reductionistic sense, no. But in a practical sense, yes, absolutely. It might sound pedantic to distinguish a variable from a parameter, and it is, in the best sense of the word. Pedant literally means teacher. Usually _pedantic_ carries a negative connotation, such as making a distinction without a difference. But here the pedant would be making a helpful distinction. For example, we might write a probability density function as _f_(_x_ ; μ, σ). The function gives the probability density at a point _x_. The density depends on parameters μ and σ, and these parameters change between applications, but for a given application they have fixed values. You find the probability of a random variable taking on values in an interval [_a_ , _b_] by integrating _f_ over that interval. When I say that, you know that I mean you’d integrate with respect to _x_ , because _f_ is a function of _x_. It is also, in an abstract sense, a function of μ and σ, but it’s typically not useful to think of it that way. Sometimes you’ll see a vertical bar rather than a semicolon to separate variables from parameters. This works out even better for probability densities because then _f_(_x_ | μ, σ) suggests the probability density of _x_ _given_ μ and σ since the vertical bar is also used for conditional probability. When I first saw a semicolon separating variables from parameters, no explanation was given, and I figured I could mentally replace the semicolon with a comma. Then later I realized that the semicolon was an act of kindness by the author giving the reader additional information.

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