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But we're talking about chapter lengths here, something that is trivially measurable.
The term "ideal chapter length" is not objective measurable term.
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The term "ideal chapter length" is not objective measurable term.
Math has much more complex tools to deal with uncertainties. Error bars, distributions, grouping based on various criteria. learn more about them.
This is exactly what is the problem - none of the stuff you suggest has remotely anything to do with what the actual question is.
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Math has much more complex tools to deal with uncertainties. Error bars, distributions, grouping based on various criteria. learn more about them.
None of them helps to clarify what "ideal chapter length" means. This is not about uncertainty in terms of probabilities, this is about the term meaning different things to different people. This is exactly what is the problem - none of the stuff you suggest has remotely anything to do with what the actual question is.
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Mathematics can only give you insight into things that can be quantified. When people try do things like (say) perform a statistical analysis of the tone of a narrative, they have to either go through and numerically quantify the tone of each passage (time-consuming & of dubious value) or feed the whole thing through sentiment analysis software (practically useless). You'll learn much more from a close subjective rea…
But we're talking about chapter lengths here, something that is trivially measurable.
Of course, these ways don't exist. "What is an effective chapter" isn't even a question with a single answer—it depends on the author's goals (to inform, to entertain, to provoke a very specific feeling, etc). So anyone who tried to pull out a "chapter idealness in relation to word count" graph in an academic context would be laughed out of the room, and justifiably so.
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None of them helps to clarify what "ideal chapter length" means. This is not about uncertainty in terms of probabilities, this is about the term meaning different things to different people. This is exactly what is the problem - none of the stuff you suggest has remotely anything to do with what the actual question is.
But somehow using more words to explain other "words" will solve the problem.
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Yes. This process is also known as "thinking about it," and it often proves useful when data-driven approaches fail.
but somehow it is unbaised and "pure".