On error analysis of my practical

AI Thread Summary
The discussion focuses on calculating the speed of light using experimental data from an LED and oscilloscope setup. The results include multiple time measurements for varying lengths of fiber optic cable, with the aim to plot L versus time. The main issue is determining the appropriate method for calculating the error in the y-values, specifically whether to use the Least Square Method with a common error or individual errors for each time measurement. The participant seeks clarification on how to approach error analysis given that time is the x-axis and L is the y-axis. Accurate error analysis is crucial since the gradient of the resulting graph represents the speed of light.
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[Urgent]On error analysis of my practical

Homework Statement


well, the aim of the practical is to calculate the speed of light using LED, oscilloscope and varying fiber optics cable.

i have my results as follows :

L /m t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 taverage

5.00 (28 30 28 28 28 28 28 28 30 28) 28.4

10.00 (60 62 60 60 60 60 60 60 60 60) 60.2

15.00 (76 76 78 76 76 76 76 76 76 76) 76.2

20.00 (102 100 102 102 102 102 102 102 100 102) 101.6

The equation used is c = n \frac{\lambda}{t}

We are to plot a graph of L versus time.

The problem now is calculating the error of y.

Do we use

Least Square Method( where \sigma_i = \sigma) OR
Least Square Method( Where each y, has its own \sigma_i)

We know that L is the y-axis in this case, however no multiple values of L has been taken. So every y, has the same \sigma. However, time has been taken mutiple times, do we use LSM(Where each y, has its own \sigma_i) on it? But time is the x-axis in this case.

So what should i use or do?

Any help will be appreciated. Thanks
 
Last edited:
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Anyway, since gradient is speed of light, the graph has to be a straight line.
 

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