Between that and simple order of magnitude approximations, it's distressing how often seemingly carefully prepared materials contain errors that can be spotted in a 5 minute reading.
Between that and simple order of magnitude approximations, it's distressing how often seemingly carefully prepared materials contain errors that can be spotted in a 5 minute reading.
It really is remarkable how many mistakes like this happen. One I've seen a lot is not knowing how percentages work, particular when it comes to changes between them. Going from 10% of something up to 15% is not a 5% increase--it's a 50% increase.
In particular I remember there were a number of breathless articles about covid vaccine side effects where they were talking about a 50% increase in incidence - from 2 in 100,000 to 3 in 100,000*. That's not something the average person needs to factor into their risk model, and headlining it as a 50% increase makes it seem more significant than it is.
*not the actual numbers, but around the right order of magnitude, fit to the example.
Just say the quantity increased "from 0.0015 to 0.002" or something.
It's particularly prevalent in news announcement of scientific studies. "New drug decreases x by 350%!"
Obviously this can and is constantly abused, but it is undeniably useful.
Is x% of y the same as y% of x?
So 14% of 50 becomes 1.4 * 5 == 7
Or to simplify even more…
1 * 5 = 5
4 * 5 = 20 -> remove the “0”
5 + 2 = 7
One significant underlying reason is that different authors make different value judgments and want to tell different narratives.
For a given set of values and narrative, there are many questions to consider, such as:
- Should a change be expressed summarized as one scalar?
- As a difference? As a division? As a percentage change? (Read https://en.wikipedia.org/wiki/Relative_change_and_difference for many ways to do it; you might be surprised at the number of ways)
- Should the initial and final quantities be specifically mentioned?
- But what are the appropriate "initial" and "final" quantities? These are tied into the goals (above).
Is a relative change best expressed as
* Divide and conquer * Abstraction * Symmetry and conservation * Proportional reasoning * Dimensional analysis * Easy cases (plugging simple values into complex formulas) * Lumping (discrete approximations of continuous functions) * Probabilistic reasoning * Springs (approximate complex systems as simple oscillators)