Applying Monte Carlo Simulation to Determine the Likelihood of Cheating on a Multiple-Choice Professional Exam
نویسنده
چکیده
This paper outlines statistical arguments used in an attempt to determine if cheating occurred on a multiple-choice exam. The arguments include the testimony in a court case involving accusations of cheating on a 100-question professional multiple-choice examination with four choices for each question. In response to the fact that the prosecution employed a witness who was an expert in statistical analysis, one of the authors was engaged by the defense to conduct an independent statistical analysis of the exam scores. The prosecution’s witness utilized a simulation to demonstrate, in his opinion, the relative certainty of cheating by the defendant in the case. The authors performed their own analysis, including simulations, to counter the testimony of the prosecution. The results presented in this paper highlight the fact that in the absence of definitive proof, in spite of a statistical analysis of data, there is still a need to make subjective interpretations when trying to decide if cheating has occurred on a multiple-choice test.
منابع مشابه
Application of Monte Carlo Simulation in the Assessment of European Call Options
In this paper, the pricing of a European call option on the underlying asset is performed by using a Monte Carlo method, one of the powerful simulation methods, where the price development of the asset is simulated and value of the claim is computed in terms of an expected value. The proposed approach, applied in Monte Carlo simulation, is based on the Black-Scholes equation which generally def...
متن کاملApplying Point Estimation and Monte Carlo Simulation Methods in Solving Probabilistic Optimal Power Flow Considering Renewable Energy Uncertainties
The increasing penetration of renewable energy results in changing the traditional power system planning and operation tools. As the generated power by the renewable energy resources are probabilistically changed, the certain power system analysis tolls cannot be applied in this case. Probabilistic optimal power flow is one of the most useful tools regarding the power system analysis in presen...
متن کاملSimulation-Based Radar Detection Methods
In this paper, radar detection based on Monte Carlo sampling is studied. Two detectors based on Importance Sampling are presented. In these detectors, called Particle Detector, the approximated likelihood ratio is calculated by Monte Carlo sampling. In the first detector, the unknown parameters are first estimated and are substituted in the likelihood ratio (like the GLRT method). In the sec...
متن کاملSimulation-Based Radar Detection Methods
In this paper, radar detection based on Monte Carlo sampling is studied. Two detectors based on Importance Sampling are presented. In these detectors, called Particle Detector, the approximated likelihood ratio is calculated by Monte Carlo sampling. In the first detector, the unknown parameters are first estimated and are substituted in the likelihood ratio (like 
the GLRT method). In the s...
متن کاملMonte Carlo Simulation to Compare Markovian and Neural Network Models for Reliability Assessment in Multiple AGV Manufacturing System
We compare two approaches for a Markovian model in flexible manufacturing systems (FMSs) using Monte Carlo simulation. The model which is a development of Fazlollahtabar and Saidi-Mehrabad (2013), considers two features of automated flexible manufacturing systems equipped with automated guided vehicle (AGV) namely, the reliability of machines and the reliability of AGVs in a multiple AGV jobsho...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009