You should look into TRIZ, which seems to be related to your idea, albeit it is mostly related to engineering (however, proponents of TRIZ try to apply it to other domains). Basically TRIZ is a collection of common engineering trade-offs that are arranged into a contradiction matrix and a set of advice how to come up with workarounds, called 40 Inventive Principles (How to use it? You are supposed to formulate your problem as a trade-off, find a relevant cell in the contradiction matrix, and look the numbers up in the list of 40 principles). However, taking the outside view, you should note that TRIZ is still relatively unknown outside the former Soviet Union. If it was as useful as it is sometimes claimed to be, wouldn’t it be very popular by now? Or was it cultural barriers that prevented it from spreading? Frankly, I don’t know.
In statistics, there is a well known Bias–variance tradeoff, which affects a wide range of situations. The trade-off between the goodness of fit of the model and its complexity (4th item in your list) is somewhat related (though not identical) to it.
A general pattern. Some trade-offs are due to Berkson’s paradox, because sometimes the situation we have is “prefiltered” by the past, and we can observe negative corellations between variables even though they are not intrinsically negatively correlated.
A special case: if we can do both X and Y, but that requires resources and we have a fixed amount of resources, then the decision how much X and how much Y should be done becomes a trade-off.
Closely related example is the trade-off between quantity and quality, e.g. r/K selection theory.
A different kind of “bias-variance” tradeoff occurs in policy-making. Take college applications. One school might admit students based only on the SAT score. Another admits students based on scores, activities, essays, etc. The first school might reject a lot of exceptional people who just happen to be bad at test-taking. The second school tries to make sure they accept those kinds of exceptional people, but in the process of doing so, they will admit more unexceptional people with bad test scores who somehow manage to impress the admissions committee. The first school is “biased” against exceptional students with bad test grades—the second school has more “variance” because by attempting to capture the students that the first school who wrongly reject, they admit more low quality students as well. You might interpret this particular example as “sensitivity vs specificity.”
Another example would be a policy for splitting tips at a restaurant. One policy would be to have all the staff split the tips equally. Another policy would be to have no splitting of tips. Splitting tips incurs bias, not splitting incurs variance. An intermediary policy would be to have each staff member keep half of their own tips, and to contribute the other half to be redistributed.
I think TRIZ has multiple reasons it’s not adopted as much as the benefits might imply due to multiple reasons, its Russian origin only one of some. The reason is also: heavily paywalled and most low-hanging fruits in technological innovation have be taken, thus the value of picking the remaining must be balanced against all the other efforts of a technological business.
You should look into TRIZ, which seems to be related to your idea
I hadn’t heard of this and it’s interesting. Thanks. In what context did you find it?
In statistics, there is a well known Bias–variance tradeoff, which affects a wide range of situations
I have it subsumed under Precision vs Simplicity; I’ll make this explicit in the next iteration.
A general pattern. Some trade-offs are due to Berkson’s paradox, because sometimes the situation we have is “prefiltered” by the past, and we can observe negative corellations between variables even though they are not intrinsically negatively correlated
Thanks, this is an interesting point, and one that I have thought about, see here.
r/k selection theory and quality vs quantity
I have these subsumed under Surely Some vs Maybe More; I’ll make this explicit in the next iteration.
A few quick thoughts.
You should look into TRIZ, which seems to be related to your idea, albeit it is mostly related to engineering (however, proponents of TRIZ try to apply it to other domains). Basically TRIZ is a collection of common engineering trade-offs that are arranged into a contradiction matrix and a set of advice how to come up with workarounds, called 40 Inventive Principles (How to use it? You are supposed to formulate your problem as a trade-off, find a relevant cell in the contradiction matrix, and look the numbers up in the list of 40 principles). However, taking the outside view, you should note that TRIZ is still relatively unknown outside the former Soviet Union. If it was as useful as it is sometimes claimed to be, wouldn’t it be very popular by now? Or was it cultural barriers that prevented it from spreading? Frankly, I don’t know.
In statistics, there is a well known Bias–variance tradeoff, which affects a wide range of situations. The trade-off between the goodness of fit of the model and its complexity (4th item in your list) is somewhat related (though not identical) to it.
A general pattern. Some trade-offs are due to Berkson’s paradox, because sometimes the situation we have is “prefiltered” by the past, and we can observe negative corellations between variables even though they are not intrinsically negatively correlated. A special case: if we can do both X and Y, but that requires resources and we have a fixed amount of resources, then the decision how much X and how much Y should be done becomes a trade-off.
Closely related example is the trade-off between quantity and quality, e.g. r/K selection theory.
A different kind of “bias-variance” tradeoff occurs in policy-making. Take college applications. One school might admit students based only on the SAT score. Another admits students based on scores, activities, essays, etc. The first school might reject a lot of exceptional people who just happen to be bad at test-taking. The second school tries to make sure they accept those kinds of exceptional people, but in the process of doing so, they will admit more unexceptional people with bad test scores who somehow manage to impress the admissions committee. The first school is “biased” against exceptional students with bad test grades—the second school has more “variance” because by attempting to capture the students that the first school who wrongly reject, they admit more low quality students as well. You might interpret this particular example as “sensitivity vs specificity.”
Another example would be a policy for splitting tips at a restaurant. One policy would be to have all the staff split the tips equally. Another policy would be to have no splitting of tips. Splitting tips incurs bias, not splitting incurs variance. An intermediary policy would be to have each staff member keep half of their own tips, and to contribute the other half to be redistributed.
Thanks, these are great examples. How did you come up with them?
I think TRIZ has multiple reasons it’s not adopted as much as the benefits might imply due to multiple reasons, its Russian origin only one of some. The reason is also: heavily paywalled and most low-hanging fruits in technological innovation have be taken, thus the value of picking the remaining must be balanced against all the other efforts of a technological business.
I hadn’t heard of this and it’s interesting. Thanks. In what context did you find it?
I have it subsumed under Precision vs Simplicity; I’ll make this explicit in the next iteration.
Thanks, this is an interesting point, and one that I have thought about, see here.
I have these subsumed under Surely Some vs Maybe More; I’ll make this explicit in the next iteration.