Z
zeshkani_usa
Prepare a plot that shows the distribution of noise in the raw DMA data
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 D10
30, 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.
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 D10
30, then you can use thefollowing 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.