Fit the raw data and determine the best equation to


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A very strange ISE probe and configuration returned this calibration voltage versus concentration via serial dilution data: {M, mV} = {{5.08356*10^+00, 1.07941*10^+00}, {5.00311*10^-01, 9.41230*10^-01}, {4.97994*10^-02, 8.43970*10^-01}, {5.06177*10^-03, 8.08500*10^-01}, {5.02806*10^-04, 6.33437*10^-01}, {4.98800*10^-05, 6.04244*10^-01}, {4.96829*10^-06, 5.25248*10^-01}, {4.92435*10^-07, 4.61175*10^-01}, {5.08715*10^-08, 3.95586*10^-01}, {5.00755*10^-09, 3.87963*10^-01}, {4.98564*10^-10, 3.33048*10^-01}, {5.07724*10^-11, 2.73206*10^-01}, {5.06794*10^-12, 2.82045*10^-01}, {4.92983*10^-13, 1.88320*10^-01}}.

Fit the raw data and determine the best equation to linearize the data (Hint: Try plotting on linear, semi-log, or log-log plots to give you a good idea where to start).

Then, find the slope, y-intercept, and correlation coefficient (R2) for the linearized equation.

Formally plot the linearized data with the superimposed fitted line with the proper title, axis labels and units, etc.

What is the unknown molar concentration of the ion if the potential is measured to be 1.08541*10^+00 mV?

Does the probe follow classic Nernst behavior for an ISE and if so what is the percent difference between your slope and the Nernst slope?

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Computer Engineering: Fit the raw data and determine the best equation to
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