Abbasi, S., & Kim, E. M., & Schubert, T. F. (2018, June), Estimation of Experimental Errors Using Monte Carlo Analysis in the Introductory Electrical Circuits Laboratory  Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30441

\bibitem{asee_peer_30441}
  Abbasi, S., \& Kim, E. M., \& Schubert, T. F. (2018, June), \emph{Estimation of Experimental Errors Using Monte Carlo Analysis in the Introductory Electrical Circuits Laboratory}
  Paper presented at 2018 ASEE Annual Conference \& Exposition , Salt Lake City, Utah.
  10.18260/1-2--30441

Shaghayegh Abbasi, Ernest M. Kim, and Thomas F. Schubert Jr. P.E..  "Estimation of Experimental Errors Using Monte Carlo Analysis in the Introductory Electrical Circuits Laboratory".  2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah, 2018, June.  ASEE Conferences, 2018.  https://peer.asee.org/30441 Internet.  15 Jan, 2025

\bibitem{asee_peer_30441}
  Shaghayegh Abbasi, Ernest M. Kim, and Thomas F. Schubert Jr. P.E..
  "Estimation of Experimental Errors Using Monte Carlo Analysis in the Introductory Electrical Circuits Laboratory".
  \emph{2018 ASEE Annual Conference \& Exposition , Salt Lake City, Utah, 2018, June}.
  ASEE Conferences, 2018.
  https://peer.asee.org/30441 Internet.  15 Jan, 2025

@INPROCEEDINGS{asee_peer_30441
author = "Shaghayegh Abbasi, Ernest M. Kim, and Thomas F. Schubert Jr. P.E."
title = "Estimation of Experimental Errors Using Monte Carlo Analysis in the Introductory Electrical Circuits Laboratory"
booktitle = "2018 ASEE Annual Conference \& Exposition "
year = "2018"
month = "June"
address = "Salt Lake City, Utah"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/30441}
number = {10.18260/1-2--30441}
}

TY  - CPAPER
AB  - It is a challenge at times to include probability and statistics in electrical engineering courses. In this student experience, experimental data was compared to statistical analysis in an Introductory Electrical Circuits Laboratory Experiment.  
Experimental data often are used to supplement engineering analysis as a basis for design. Not all data are equally good: errors are a part of every engineering experiment. Gross errors and statistical errors comprise the two major groups of experimental error. Gross errors are due to mistakes made by the humans that conduct the experiments and tests. An example of a gross error is reading the incorrect scale on a meter. Statistical errors are due to randomness in measurement processes, component values, and equipment inaccuracies. 
The goal of this experiment in the Introductory Electrical Circuits laboratory was to estimate the uncertainty in experimental measurements and calculated results due to random errors. Single resistor variations in DC electric circuits was used to determine variable uncertainty intervals. The data was used to determine errors in variable values and their effect on measured quantities.
Each group’s measured values were recorded and histograms of those values were plotted. They were then compared to the data collected by the entire laboratory section and composite histograms produced. Experimental results were then compared to the results of a MultiSim Monte Carlo circuit simulation.
This paper presents the laboratory experiment and procedure, results of student experiments, and assessment of student learning in this required sophomore engineering class and laboratory.

AU  - Shaghayegh Abbasi
AU  - Ernest M. Kim
AU  - Thomas F. Schubert Jr. P.E.
CY  - Salt Lake City, Utah
DA  - 2018/06/23
PB  - ASEE Conferences
TI  - Estimation of Experimental Errors Using Monte Carlo Analysis in the Introductory Electrical Circuits Laboratory
UR  - https://peer.asee.org/30441
DO  - 10.18260/1-2--30441
ER  -