Curve fitting for Gravity/Conservation of Energy Lab

In summary, the problem has to do with sig figs going down to 1. I've checked them multiple times by hand and with sigfig calculators but it is all the same. With 1 sig fig my standard deviation ends up being 0 which I am not sure that is acceptable.
  • #1
Dietrichw
22
0

Homework Statement


[/B]
The problem has to do with sig figs going down to 1. I've checked them multiple times by hand and with sigfig calculators but it is all the same. With 1 sig fig my standard deviation ends up being 0 which I am not sure that is acceptable.
It makes sense as the points are super consistent for measuring G but when it comes to filling out the tables having 0 for most parts bothers me.

Homework Equations


V^2=g(2H)
Y=mx+b

The Attempt at a Solution


I have an excel document with all my data and calculations
 

Attachments

  • measuring g.xlsx
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  • #2
It seems that you calculated the h (or Δh) values incorrectly since you are using the same angle, θ or L2, for each run? Or did you keep the angle the same and released the glider at progressively lower points along the track?
 
Last edited:
  • #3
andrevdh said:
It seems that you calculated the h (or Δh) values incorrectly since you are using the same angle, θ or L2, for each run? Or did you keep the angle the same and released the glider at progressively lower points along the track?
We kept the angle the same and changed the release point for each set of runs
 
  • #4
0 is not the same as an error in one significant figure.
One significant figure means you take the first nonzero digit, so your ##\sigma_g## is 0.06

(In case the first nonzero digit is a 1, we often take the first two digits - because the step from 1 to 2 is so big - and still speak of one significant digit. But it depends: with the relative error in the sigma approximately ##1/\sqrt N## and 5 observations you understand that ##\sigma## itself isn't very accurate at all)​

So as a result you have ##g = 9.56 \pm 0.06 ## m/s2 for the light glider - and have to say something reasonable about the intercept ##0.055 \pm 0.024## (here I show two digits -- the intercept is 2##\sigma## from zero, which may or may not give you a reason to fit y = m x instead of y = mx + b) .
 
  • #5
I forgot something -- how accurate is your theta ? This is a systematic error (all h are affected the same way by a deviation from the actual theta), so it has to be folded into the error you calculated for g (in fact you have determined ##g/\sin\theta## and report ##g## -- a 1% error in ##\theta## already dominates the statistical error ! You could be very sophisticated and report ## g = 9.56 \pm 0.06\, (\text stat) \pm 0.1 \,(\text syst) ## m/s2 . But I wonder if teacher will appreciate it...
 

1. What is curve fitting and why is it important in the Gravity/Conservation of Energy Lab?

Curve fitting is a statistical method used to find the best-fit line or curve that represents a set of data points. In the Gravity/Conservation of Energy Lab, it is important because it allows us to determine the relationship between variables (such as distance and time) and make predictions based on the data.

2. How do you choose the best-fit line or curve in curve fitting for this lab?

The best-fit line or curve is chosen by minimizing the distance between the data points and the line or curve. This can be done by using mathematical techniques such as the least squares method or by using software that can automatically generate a best-fit line.

3. Is curve fitting accurate and reliable in the Gravity/Conservation of Energy Lab?

Curve fitting is a useful tool for analyzing data, but its accuracy and reliability depend on the quality of the data and the assumptions made during the fitting process. It is important to carefully consider the limitations and uncertainties in the data and the chosen curve fitting method.

4. Can curve fitting be used to make predictions beyond the collected data points?

Yes, curve fitting can be used to make predictions beyond the collected data points. However, the accuracy of these predictions depends on the quality of the data and the assumptions made during the fitting process.

5. Are there any common pitfalls or mistakes to avoid when using curve fitting in the Gravity/Conservation of Energy Lab?

One common mistake is overfitting the data, which occurs when a complex curve is used to fit a relatively small amount of data points. This can lead to inaccurate predictions and should be avoided. It is also important to carefully consider the assumptions and limitations of the chosen curve fitting method and to validate the results with additional experiments.

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