Can plotting corrected values help determine a more precise E_g?

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In summary, the conversation discusses the equation ##qV = E_g + T[kln(\frac{I}{A}) - (3 + \frac{\gamma}{2})kln(T)]## and its corrected value, ##qV_c = qV + (3 + \frac{\gamma}{2})kTln(T)##, which can be used to obtain a more accurate value for ##E_g##. It is determined that plotting ##qV_c = E_g + kTln(\frac{I}{A})## against ##T## will yield a linear graph and the intercept of this graph will be the accurate value of ##E_g##.
  • #1
Kara386
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I have the equation

##qV = E_g + T[kln(\frac{I}{A}) - (3 + \frac{\gamma}{2})kln(T)]##

So if I plot ##qV## against ##T## that'll be a straight line with the y-intercept being ##E_g##. But then my lab manual says a more precise value of ##E_g## can be found by plotting the corrected value

##qV_c = qV + (3 + \frac{\gamma}{2})kTln(T)##

So does that mean if I want to plot ##qV_c## against ##T##, which I think is what's being asked, then I should plot

##qV_c = E_g + kTln(\frac{I}{A})##

And I'll get my more accurate ##E_g##?
 
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  • #2
Hi,

You can't plot ##E_g## to find ##E_g##. (which probably is also not how I should understand your last line (*))

Your first
Kara386 said:
So if I plot ##qV## against ##T## that'll be a straight line
ignores the ##
- (3 + \frac{\gamma}{2})kln(T)## in the full ##qV## expression. I suppose this is a small disturbance (?) and ##qV_c## is an attempt to get a more linear relationship.

You really want to plot ##qV_c## against ##T## ((*) which I think is how I should understand your last sentence).

But of course, the proof of the pudding is in the eating. Does it indeed yield a more linear graph ?

PS if you want to avoid things like ##kln## in ##\TeX## use \ln to get ##k\ln##
 
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  • #3
BvU said:
Hi,

You can't plot ##E_g## to find ##E_g##. (which probably is also not how I should understand your last line (*))

Your first
ignores the ##
- (3 + \frac{\gamma}{2})kln(T)## in the full ##qV## expression. I suppose this is a small disturbance (?) and ##qV_c## is an attempt to get a more linear relationship.

You really want to plot ##qV_c## against ##T## ((*) which I think is how I should understand your last sentence).

But of course, the proof of the pudding is in the eating. Does it indeed yield a more linear graph ?

PS if you want to avoid things like ##kln## in ##\TeX## use \ln to get ##k\ln##

Sorry, should have made it clearer. :) As you thought, I meant I'll plot the corrected value of ##qV_c## against ##T## and the intercept of that graph will be my more accurate ##E_g##. I think I can consider the ##- (3 + \frac{\gamma}{2})kln(T)## to be constant for ##T## in the range 200 to 400 Kelvin, where all measurements will be taken, but probably the correction tries to deal with inaccuracies caused by that assumption. And thanks for the tip, I'll switch to ##\ln## in future!
 
  • #4
Plotting your first equation vs. T will not give a straight line as there is a ln(T) term. Plotting

##qV_c = qV + (3 + \frac{\gamma}{2})kTln(T)##

vs. T will give a straight line since T is now appearing linearly on the right hand side of the equation. The intercept of that straight line on the vertical axis will be Eg.
 
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  • #5
pixel said:
Plotting your first equation vs. T will not give a straight line as there is a ln(T) term. Plotting

##qV_c = qV + (3 + \frac{\gamma}{2})kTln(T)##

vs. T will give a straight line since T is now appearing linearly on the right hand side of the equation. The intercept of that straight line on the vertical axis will be Eg.
If I sub ##qV = qV_c - (3 + \frac{\gamma}{2})kT\ln(T)## into my first equation, that gives

##qV_c = E_g + kT\ln(\frac{I}{A})##

Which is linear in ##T##. Are you saying that's what I should plot, or just plot

##qV_c = qV + (3 + \frac{\gamma}{2})kTln(T)##?
 
  • #6
How about doing it instead of asking ?
 
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  • #7
Kara386 said:
If I sub ##qV = qV_c - (3 + \frac{\gamma}{2})kT\ln(T)## into my first equation, that gives

##qV_c = E_g + kT\ln(\frac{I}{A})##

Which is linear in ##T##. Are you saying that's what I should plot, or just plot

##qV_c = qV + (3 + \frac{\gamma}{2})kTln(T)##?

Please note that only this equation

[tex]qV_c = E_g + kT\ln(\frac{I}{A})[/tex]

will give you a linear equation in T if you plot qVc versus T. All the others that you wrote have extra "T" hanging around elsewhere in the equation.

Zz.
 
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  • #8
BvU said:
How about doing it instead of asking ?
I don't actually have any data yet. And I know only one of the equations is linear, therefore must be the right one, so checking which one to plot was unecessary except for my peace of mind, I suppose. Bad habit of mine. Thanks for your help everyone! :)
 

Related to Can plotting corrected values help determine a more precise E_g?

1. What is the purpose of plotting corrected values?

The purpose of plotting corrected values is to visualize the relationship between two variables while taking into account potential confounding factors or errors in measurement. This allows for a more accurate analysis and interpretation of the data.

2. How do you determine the corrected values to plot?

The corrected values to plot are typically determined through statistical methods, such as regression analysis, that take into account the potential confounding factors or errors in measurement. These methods aim to adjust the data to reflect the true relationship between the variables of interest.

3. Can plotting corrected values change the overall interpretation of the data?

Yes, plotting corrected values can change the overall interpretation of the data. By accounting for confounding factors or errors in measurement, the corrected values may reveal a different relationship between the variables than initially observed. This can lead to a different interpretation of the data and potentially different conclusions.

4. Are there any limitations to plotting corrected values?

Like any statistical method, there are limitations to plotting corrected values. The accuracy of the corrections depends on the accuracy of the data and the chosen statistical methods. Additionally, the corrections may not account for all potential confounding factors or errors, leading to potential biases in the interpretation of the data.

5. How can plotting corrected values benefit scientific research?

Plotting corrected values can benefit scientific research by improving the accuracy and reliability of the data analysis. By accounting for potential confounding factors or errors, the results of the study can be more trustworthy and can lead to more accurate conclusions. This can also help to identify areas for further research and potential improvements in study design.

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