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

• PancakeSyrup
In summary, the conversation discusses creating two best fit lines for a set of data and finding the value of absolute zero for both. One best fit line is to be made assuming no uncertainty in P, while the other assumes uncertainty. The question of whether the best fit line should be the same in both cases and how to find the error is raised. The conversation also mentions the purpose of regression and the level of error analysis expected in the class.
PancakeSyrup
Member advised to use the homework template for posts in the homework sections of PF.
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.

PancakeSyrup said:
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?

Student100 said:
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.

## 1. What is the significance of finding absolute zero values from best fit lines?

Finding absolute zero values from best fit lines is important in understanding the relationship between two variables. It allows us to determine the point at which one variable becomes completely independent of the other, and provides valuable information about the accuracy of our data and the strength of the relationship between the variables.

## 2. How do you calculate absolute zero values from best fit lines?

To calculate absolute zero values from best fit lines, you will need to plot the data points on a graph and draw a best fit line that closely follows the trend of the data. Then, you can use the slope-intercept form of a line (y = mx + b) to determine the y-intercept, which represents the absolute zero value on the y-axis. If there is uncertainty in the data, you can also use a regression analysis to calculate the absolute zero value.

## 3. Can you determine absolute zero values from best fit lines without uncertainty?

Yes, it is possible to determine absolute zero values from best fit lines without uncertainty. However, the accuracy of the results may be affected by any systematic errors in the data. It is always recommended to use regression analysis or other statistical methods to account for uncertainty and improve the accuracy of the absolute zero values.

## 4. What is the role of uncertainty when finding absolute zero values from best fit lines?

Uncertainty plays a significant role in finding absolute zero values from best fit lines as it indicates the range of possible values for the absolute zero point. Accounting for uncertainty helps to improve the accuracy of the results and provides a more realistic representation of the relationship between the variables.

## 5. How can finding absolute zero values from best fit lines be useful in scientific research?

Finding absolute zero values from best fit lines can be useful in a variety of scientific research fields. It can help to determine the accuracy and reliability of experimental data, identify trends and patterns between variables, and provide valuable insights into the behavior of physical systems. It can also aid in making predictions and developing new theories and hypotheses.

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