Lab 1 PHYS 217 (2)

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Texas A&M University *

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217

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English

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Dec 6, 2023

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pdf

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3

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LAB 1: INTRO TO DAQ & UNCERTAINTY Stephen Adcox, Sean Gambrell, Lexi Knoerzer Texas A&M University College Station, TX 77843, US. Abstract : This report covers the general concept of error propagation and introduces new data collection equipment, the DAQ. By using the DAQ to take 1000 samples of a known voltage and then 1000 samples of an unknown voltage, they can be used to create a plot of sample number (N) vs. average voltage (V). Furthermore, the total sample uncertainty of the known and unknown can be calculated, plotted, and then compared. This lab gives an idea of the uncertainty in the DAQ and data collection methods. Keywords: Uncertainty, Voltage, Average, Sample 1. Introduction In this lab, groups were to analyze how increasing the sample size would affect our calculated uncertainty. During this experiment, one thousand different samples of the voltage and added each one to our calculated average voltage using equation 1. This allowed for the groups to see the uncertainty change as the sample size increased. This is found using equation 2. Because sample size (n) is in the denominator the percentage of uncertainty decreases as the sample size increases. Based on this, we can see that the more sample sizes are added to the experiment the more certain we can be of our average voltage. 2. Experimental Procedure The setup began by connecting a laptop to MobaXTerm and the DAQ, voltage measurement system, at each table. In the first trial, a sample of known voltage was to be collected. This was done by setting the DAQ to a known voltage and running the given code in MobaXTerm. A trial consisting of 1000 samples of known voltage would be taken. The file would then be saved for later use in calculations. Next for trial 2, a sample for a mystery voltage was collected. By using the second set of given code, we launched the lab.mystery_voltage script in MobaXTerm. After running the script, users selected USB0 to connect to the power supply, after which the DAQ screen would go blank and take 1000 samples of some unknown voltage, V. This file should also be saved for later calculations. The end result of the data collection should be two files, both consisting of 1000 samples, 1 of known voltage and 1 of unknown. 3. Results and Analysis Beginning with Equation 1, teams used this equation to smooth out the data of the known and unknown voltage and then create Figure 1 and Figure 3, respectively. These plots explicitly showed the differences between smooth data and experimental data that may have outliers. Then the command STDEV ($A$1: An)/sqrt(n) was used in excel to mimic Equation 3 to find the Standard Deviation. The Standard Deviation was then plugged into Equation 2 to find the Uncertainty of the Voltage. The Uncertainty was then plotted to create Figure 2 and Figure 4 . The average of each data point was taken to find the average voltage in Table 1 . Table 1 Type Average Voltage Uncertanty Known Voltage 1 V Unknown Voltage 2.87 V 0.0143 Equation 1
Equation 2 Equation 3 Figure 1 Figure 2
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