The terminology "G is only a function of...."

In summary, saying "##G## is only a function of ##x_1,x_2,x_3##" means that ##G## can be expressed as a function of ##x_1,x_2,x_3## and is not constant with respect to any other variables. This is the most common interpretation, although it is possible for ##G## to be constant with respect to some variables in certain regions of its domain. It is important to be precise and simple when declaring the dependence of ##G## on variables.
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Stephen Tashi
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For example, if we have a set of variables x1, x2,...xn, what does it mean to say "G is only a function of x1,x2,x3"?
If we have a set of variables ##x_1, x_2, ...x_n ## what does it mean to say that "##G## is only a function of ##x_1,x_2,x_3##"?

My thoughts:

Context 1: The function ##G## has been previously defined.

In Context 1, saying "##G## is only a function of ##x_1,x_2,x_3##" means the same thing as the usual interpretation of "##G## is a function of ##x_1,x_2,x_3## , namely that ##\{x_1,x_2,x_3\}## is exactly the set of arguments for ##G## ( rather than being a proper subset of the arguments for ##G##).

Context 2: ##G## represents the measurement of some physical phenomenon such as temperature or speed.

Possibiity 2 a) ##G## can be expressed as a function of ##x_1,x_2,x_3## However ##G## might be constant with respect to some of those variables.

Possibility 2 b) ##G## can be expressed as a function of ##x_1,x_2,x_3## and ##G## is not constant with respect to any of those variables.

I think possibility 2 b) is the most common interpretation.
 
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My vote - 2a).
 
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Possibility 3) G does not depend on x4 to xn.

You would typically expect it to be not constant with respect to x1 to x3 everywhere (but it might still be constant with respect to these in some regions of the domain).
 
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Declare simply ##G=G(x_1,x_2,x_3)## and that's the end of it. If we say it only depends on these variables, that's going to open another can of worms. E.g if ##G## was almost constant w.r.t some variable, in some contexts it could be viewed as NOT being dependant on that variable. Keep it simple, be precise.
 
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FAQ: The terminology "G is only a function of...."

What does "G is only a function of..." mean?

The phrase "G is only a function of..." means that the variable G, which represents a certain quantity or value, is solely dependent on or determined by the other variables or factors mentioned after the phrase. In other words, G does not have any other independent variables affecting it.

Why is it important to specify that "G is only a function of..."?

Specifying that "G is only a function of..." is important because it helps clarify the relationship between G and the other variables. It also helps in accurately predicting or calculating the value of G, as it eliminates any potential confusion or errors caused by other independent variables.

What are some examples of "G is only a function of..."?

Some examples of "G is only a function of..." include the ideal gas law, where pressure (P) is only a function of temperature (T) and volume (V); the formula for calculating gravitational potential energy, where mass (m) is only a function of height (h) and gravitational acceleration (g); and the formula for calculating the period of a pendulum, where the length (L) is only a function of gravitational acceleration (g).

Can "G is only a function of..." be applied to any scientific equation or formula?

Yes, "G is only a function of..." can be applied to many scientific equations or formulas, particularly those that involve only a few variables and have a clear relationship between them. However, there may be cases where G is a function of multiple variables, and in such cases, it is important to specify which variables are the independent ones.

How does understanding "G is only a function of..." contribute to scientific research?

Understanding "G is only a function of..." is crucial in scientific research as it helps in accurately interpreting and analyzing data, making predictions, and developing theories. It also allows scientists to identify and control any potential confounding variables that may affect the outcome of their experiments or studies.

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