Boxcar Averaging Exercises
- Page ID
- 77552
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Boxcar Averaging Exercise #1
A boxcar averaging spreadsheet similar to the Ensemble Averaging spreadsheet can be accessed by clicking here.
- Adjust the following parameters in the boxcar averaging spread sheet:
- Peak Intensity = 5 μV (All 3 peaks)
- Peak #1 Mean & Standard Deviation (1.000 ± 0.005) min
- Peak #2 Mean & Standard Deviation = (2.000 ± 0.025) min
- Peak #3 Mean & Standard Deviation = (3.000 ± 0.250) min
- Noise = 2 μV
- Adjust the number of boxcar elements for each dataset
- Top = 9 data points
- Middle = 3 data points
- Bottom = 1 data point (raw data)
- Which of the peak parameters is the most significant when using boxcar averaging to increase S/N? Support your choice based on what you observe in the boxcar averaging spreadsheet.
Boxcar Averaging Exercise #2
- Adjust the following parameters in the boxcar averaging spreadsheet:
- Peak Intensity = 4 μV (Peak #1), 2.5 μV (Peak #2), 1 μV (Peak #3)
- Peak #1 Mean & Standard Deviation = (1.00 ± 0.15) min
- Peak #2 Mean & Standard Deviation = (2.00 ± 0.15) min
- Peak #3 Mean & Standard Deviation = (4.00 ± 0.15) min
- Noise = 2.0 μV
- Adjust the number of boxcar elements for each dataset
- Top = 9 data points
- Middle = 5 data points
- Bottom = 1 data point (raw data)
- Discuss the ability of boxcar filters to clearly extract signals from noise at or below the detection limit based on S/N enhancement.