Finding Absolute Zero Values from Best Fit Lines with & w/o Uncertainty

[PancakeSyrup]

In one of my problems, I have this set of data.

I have to create two best fit lines, and find a value of absolute zero for both.

The first best fit line is to be made assuming there is NO uncertainty in P. This is rather straightforward, just use the normal linear regression, find a slope and find a y-intercept, and there should be no error on either of them.

The second best fit line is to be made assuming there IS uncertainty in P. Am I incorrect in thinking that the best fit line should be exactly the same as the other one, except there would be an error in the slope and y-intercept?
And how would I find this error in them both?Also, I'm not sure if this is posted in the right section, if not please move this to the appropriate section.

 

[Student100]

In one of my problems, I have this set of data.

View attachment 110417

I have to create two best fit lines, and find a value of absolute zero for both.

The first best fit line is to be made assuming there is NO uncertainty in P. This is rather straightforward, just use the normal linear regression, find a slope and find a y-intercept, and there should be no error on either of them.

There is error in the strictest sense, that is the whole purpose behind regression, to minimize it.

The second best fit line is to be made assuming there IS uncertainty in P. Am I incorrect in thinking that the best fit line should be exactly the same as the other one, except there would be an error in the slope and y-intercept?
And how would I find this error in them both?Also, I'm not sure if this is posted in the right section, if not please move this to the appropriate section.

This really depends on what's expected of you. So, yes, what you said is probably what the professor expects from just the information in the post. Find the best fit line and then carry the error over into the slope and y-intercept.

This isn't the easiest question to answer, because it's hard to judge how much error analysis is expected of you, or what you already know. What class is this for?

 

[PancakeSyrup]

There is error in the strictest sense, that is the whole purpose behind regression, to minimize it.
This really depends on what's expected of you. So, yes, what you said is probably what the professor expects from just the information in the post. Find the best fit line and then carry the error over into the slope and y-intercept.

This isn't the easiest question to answer, because it's hard to judge how much error analysis is expected of you, or what you already know. What class is this for?

This is the lab section for undergraduate University Physics 3.