higbvuyb
100+ Head-Fier
- Joined
- Jul 7, 2009
- Posts
- 339
- Likes
- 43
I think your view and understanding of models is too narrow. Note that models come in different forms, and some are more specific and parameterized, while some contain unknown variables.
For example, you can do the math in a linear systems textbook, and you will find that you can make a lot of predictions about how linear systems behave that are generalized to all linear systems. You don't need to know the FR specifically. That's one kind of model.
Measuring FR of a specific device involves taking the math and using it to fit observations, and compute the FR. What you end up with is a more specific model.
That's not relevant to the point being made. Assuming that something acts linearly would be applying a specific model to the data. However, that does not make the data into a model, much like petrol isn't a car just because the car is using it.
First of all, you aren't arguing that measurements aren't models, you are just arguing that they are very good models. Sometimes they are. As far as models of audio equipment, they are only useful insofar as they have been "rigorously" correlated with hearing.
You didn't understand. This is a side point; some models are rigorously tested and well understood, minimising the assumptions required to use them.
This has nothing to do with measurements being models or whatever. "a voltmeter measures voltage" is a model but it certainly isn't a measurement.
Of course it's a model of hearing. An FR with a big peak in the bass is roughly correlated with the listening experience we report as "loud bass." It's a rough model, but this is a very important fact, because as I said, models in audio are only useful insofar as they have been correlated with the listener's experience.
No, the model being used is your assumption that a bass peak correlates with hearing loud bass. The measurement just gives you a number. It doesn't stand behind you with a baseball bat, telling you "you must interpret the data this way with these assumptions"
This isn't a difficult concept! Read this again and think about it until you understand the distinction being made here.
The measurement is the data.
Models are used to interpret data. Data is not a model. As with your above post, you keep incorrectly conflating the data itself with how you are interpreting it.