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Data Analysis Homework You are attempting to calculate the concentration of an i

ID: 718000 • Letter: D

Question

Data Analysis Homework You are attempting to calculate the concentration of an iron complex you have synthesized. You create a series of eight standard solutions from a single stock solution and measure the absorbance of each sample at 325 nm. You have also prepared five sample solutions and you have recorded the absorbance of each sample at the same wavelength. Using the absorbance measurements below construct a calbration curve Determine the concentration of your unknown sample as measured by the UV-Vis spectrometer, the uncertainty in that value and the 95 % confidence interval. Make sure to test for any gross errors in the data (standard and/or sample). Absorbance Standard Concentration (ppm) 0.501 ppm 0.802 ppm 1.002 ppm 1.503 ppm 2.004 ppm 0.1094 0.1629 0.1889 0.4321 0.4121 0.4793 0.6225 0.7812 2.505 3.502 ppm 4.008 ppm sample sample sample sample 0.3999 0.4056 0.4082 0.3675 0.3993 Write-up your analysis in the form of a results section. You should include examples of your calculations and descriptions of how you decided (if you did) to remove any gross errors from your data.

Explanation / Answer

A plot of concentration (x -axis) and absorbance (y-axis) has been obtained using Excel. A linear fitting is done using regression analysis tool in Excel. The plot and line equation is shown.

R2 value is 0.95 or 95%.

The absolute error between experimental and linear model equation are predicted as:

The data point for concentration 1.503 ppm shows the largest error. The predicted concentration using linear equation are calculated for samples:

The uncertainity in data is to within +- 0.12 ppm (absolute).

The error can be reduced by repeating the experiment three times and considering the average of all measurement.

Conc. (ppm) Absorbance Abs error 0.501 0.1094 -0.02443 0.802 0.1629 -0.02484 1.002 0.1889 -0.03466 1.503 0.4321 0.118813 2.004 0.4121 0.009084 2.505 0.4793 -0.01345 3.502 0.6225 -0.04881 4.008 0.7812 0.019267