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#### zeshkani_usa

set. To do this, you will need to establish a set of bins to

accumulate the number of observations for a range of intensity values.

For the intensities in DMA.txt, use bins that range from 2.7815 -

2.7715 with an increment of 0.0005 volts, which will provide 21 bins

for the analysis. Use the Excel Frequency command to determine the

number of observations that fit into each bin. The correct syntax is:

=Frequency(data_array, bins_array), where data array is the array of

cells with the observations and bins array is the cells with the

assigned bins. See the helpful hints below for more details and use

the Excel Help window for more information.

Output of the Frequency command provides the number of observations

that fall into each bin. Now, compute the relative frequency by

dividing each of the frequencies by the sum of all frequencies. If

your frequencies are listed in cells D1030, then you can use the

following command in cell E10=D10/Sum($D$10:$D$30). This formula can

be copied into the remaining cells (E11 - E30).

Now, compute the Gaussian distribution for these data by using the

Normdist command that was used in Problem I. A Normdist value should

be calculated for each bin by using the following syntax:

=normdist(C10, mean, stdev, false), where C10 corresponds to the point

along the x-axis of the distribution plot, and the mean and standard

deviation are for the full set of 5000 data points given for each data

set. These values (mean and standard deviation) were calculated for

the raw data in Problem III. False indicates you do not want the

cumulative value, but the discrete value at point C10. Calculate the

relative Gaussian distribution by using the same strategy described

above for the relative frequency.

Plot these distributions as Column Plots using the bins as x-values and

the relative frequency and relative Gaussian distribution values as

y-values. Now, right-click on one of the Gaussian columns in your plot

and change the chart-type to Line, and select lines with no data

points. This should result in a line that shows the Gaussian

distribution superimposed on the measured intensity distribution.