(Solved) : Trusted Python B 25 N N Run C Code 1 Import Matplotlibpyplot Plt 2 Pltplot 1000 2000 3200 Q42703901 . . .

Trusted Python + B In [25]: N + N Run C Code 1 import matplotlib.pyplot as plt 2 plt.plot([1000, 2000, 3200, 4000, 5000, 6000, 7000,0000 9000, 10000 3 0.13152981,0.11591196,0.13149285,0.13802004]) 4 plt.xlabel(‘Number of Elements) 5 plt.ylabel(“Time Elapse in seconds) 6 plt.show() 10.02898169,0.64497409,.03900313,0.12191725,0.06650281, 0.141 seconds The Elapse 00000000 Number of timents Fitting curve Using one regression tool to find parameters w, and in function () = + log() that best fits the results you obtained above. You can then plot another figure that include both the original results and a fitting curve Show transcribed image text Trusted Python + B In [25]: N + N Run C Code 1 import matplotlib.pyplot as plt 2 plt.plot([1000, 2000, 3200, 4000, 5000, 6000, 7000,0000 9000, 10000 3 0.13152981,0.11591196,0.13149285,0.13802004]) 4 plt.xlabel(‘Number of Elements) 5 plt.ylabel(“Time Elapse in seconds) 6 plt.show() 10.02898169,0.64497409,.03900313,0.12191725,0.06650281, 0.141 seconds The Elapse 00000000 Number of timents Fitting curve Using one regression tool to find parameters w, and in function () = + log() that best fits the results you obtained above. You can then plot another figure that include both the original results and a fitting curve

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Answer to Trusted Python + B In [25]: N + N Run C Code 1 import matplotlib.pyplot as plt 2 plt.plot([1000, 2000, 3200, 4000, 5000,…