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Least squares fit using Ohm's law The file current measurements.txt, contains a set of six measurements of the current as a function of the

Least squares fit using Ohm's law The file current measurements.txt, contains a set of six measurements of current_measurements.txt 1.0 1.3 3.0 2.2 5.0 2.9 7.0 3.9 9.0 5.05 11.0 6.23

Least squares fit using Ohm's law The file current measurements.txt, contains a set of six measurements of the current as a function of the voltage to measure the resistance, R. The first column is the voltage value in V and the second column is the current value in A. The uncertainty for each measurement is 0.2A. (a) Plot the current measurements as a function of the voltage. (b) Write a function which calculates the x value for an evaluated function, data points and an uncertainty. Write another function representing Ohm's law. Then, write a function that loads the data, evaluates ohm's law and the x2 as a function of the resistance, R. (e) Plot this x function as a function of the resistance and use the plot to find the minimum value of the x- and therefore the best fit value of R. (d) Compare this best fit value to the one you obtain using the analytical formulae described in the lecture for linear regression. Do they agree? If not, why? (e) Read off the uncertainties on R by using the A(x)= 1 rule. Does this agree with the analytical formula shown in the lecture? current_measurements.txt 1.0 1.3 3.0 2.2 5.0 2.9 7.0 3.9 9.0 5.05 11.0 6.23

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a Plot the current measurements as a function of the voltage import matplotlibpyplot as plt import numpy as np Load data from file data nploadtxtcurre... blur-text-image

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