Using Statistics to Fool Juries
Using statistics to fool juries can have devastating consequences in a criminal trial. A jury’s mistake in interpreting statistics can send an innocent person to jail, or release a guilty person back into society. Juries need to understand the background of the evidence and the correct statistical data prior to making a verdict.
Coin toss experiment and answers to the questions.
The experiment described in the video asked three questions: True or False.
1. The average number of coin flips until heads, tails, and heads result is larger than the average number of tosses resulting in heads, tails, and tails. My answer was false, and the correct answer is true.
2. The average number of coin flips resulting in heads, tails, and heads is the same as the average number of tosses until heads, tails, and tails. My answer was false and was right.
3. The average number of coin flips resulting in heads, tails, and heads are smaller than the average of tosses until heads, tails, and tails. My answer was true and was right.
Surprised by the right answers.
When I answered the questions, I initially approached the questions by thinking about probability. I assumed the probability of each coin flip has a 50% chance of being heads or tails.
I did not consider the repeatability of heads, tails, and tails in order to make the first question true.
“Once you have listed all possible results, then you can work out the probabilities quite easily. Say that you are going to toss three coins, and you want to work out the probability of only one head (and so two tails). The possible results are: TTT, TTH, THT, THH, HTT, HTH, HHT, HHH. All these results are different, and they are all...
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... is guilty against the probability of their innocence will send a defendant to jail.
Conclusion
Not all juries are easily fooled. It takes strong expert testimony to convict a person on the probability they committed a crime. Most people that see a statistic that is overwhelming favors the probability of an event happening will agree with that probability. Juries will be presented with statistics, and percentages. They will have to decide what is correct and was is not in order to come up with the right verdict.
References
Edkins, J. (2007). Tossing coins - theory. Probability. Retrieved April 14, 2014, from http://gwydir.demon.co.uk/jo/probability/info.htm
Brown, S. (2013, February 3). Medical False Positives and False Negatives / MATH200 / Brown, TC3. Retrieved April 14, 2014, from http://www.tc3.edu/instruct/sbrown/stat/falsepos.htm
Based on the possible outcomes (assuming the contestant always chooses to switch) featured above, if the contestant switches they have a 7/18, or
Our conclusion is that while a rise in each stat had some affect in the rise or fall of winning percentage, we could not determine a single stat that had a direct affect on the dependent variable (Winning Percentage). Our results were more effective when we ran the test on how the combination of all stats affected winning percentage, however, this would be obvious given the nature of our study.
A juror who has no experience with or background knowledge on the subject of forensic science is a rarity in this day and age. In 2006, 70 million people watched one of the three versions of CSI in one week and 30 million watched the original CSI in one night (Shelton). Thanks to these popular television shows people are beginning to think they have certain knowledge about the way a case should be investigated and what scientific evidence needs to be provided in court. The worst thing about the CSI Effect is that “jurors think they have a thorough understanding ...
Introduction to the basic concepts of probability and statistics with discussion of applications to computer science.
...T. M. (1997). Can the jury disregard that information? The use of suspicion to reduce the prejudicial effects of retrial publicity and inadmissible testimony. Personality and Social Psychology Bulletin, 23(11), 1215-1226.
Risinger, D. Michael. "INNOCENTS CONVICTED: AN EMPIRICALLY JUSTIFIED FACTUAL WRONGFUL CONVICTION RATE." Journal of Criminal Law & Criminology 97.3 (2007): 761-806. Legal Collection. EBSCO. Web. 2 Mar. 2011
First we are going to talk about probability theory, which has to do with mathematics and analysis of random phenomena. You are probably used to putting the number of outcomes over the total amount of the object or total amount what you have. An example is, if you have a normal dice and you want the probability of rolling an odd number, you would take the total amount of odd numbers (3) and put that over the total (6) amount of numbers on the dice like so 3/6 which you can also reduce it to ½ because 3 is half of 6. This theory has been around since the sixteenth century and started off as the outcome you would get in a game, which was created by Pierre de Fermat, Blaise Pascal and Gerolamo Cardano. Later on in the seventeenth century Christiaan Huygens published a book on the subject.
Our current trial by jury system was originally adopted from Anglo-Saxon English common law. Prior to juries, the United States had much more rudimentary methods that were in affect, such as bench trials. A bench trial consists of solely the judge determining the final verdict, versus a jury possessing that responsibility. Proceeding with a trial by jury assures that there will be a margin of error, simply due to the fact that the jurors are human, and are susceptible to human fallibility. Whether the jury is cognizant of it or not, emotions such as pre-determined bias and favoritism can impede or bring the case to a halt all together. According to Andy Leipold, a professor emeritus at the University of Illinois College of Law, the number of jury trial conviction rates have increased from 75 percent in 1946 to 84 percent from 1989 to 2002 (Krause). This sudden anomaly can be attributed to the influx of uneducated jurors, the increased cost of proceeding to trial, and improper juror selection.
Lieberman in Scientific Jury Selection states, “...scientific jury selection originated in criminal trials in which academic researchers provided assistance to defense counsel because the researchers were concerned about the government having disproportionate degree of power and control over the outcome of cases.” As stated before, a jury does not have to think about the laws or the influence of the judge and lawyers, they must simply agree on what they believe happened. Some juries depend on facts or evidence, while others decide on if they believe the story others decide on their moral stances. This all comes back into why psychology is so important in the process of jury selection. When a juror decides the fate of an individual they don’t necessarily just use their brain, they use their heart, or their beliefs. What someone believes in can only be interpreted through psychology, the scientific study of the human mind and its functions, especially those affecting behavior in a given context. Trying to predict the outcome of someone's decisions is very difficult, that's why we have so many specialists, and consultants that are used in trials to determine the best possible pathway for a criminal
in Houck). Jurors who are influenced by the CSI Effect tend to have biased opinions because CSI shows are the basis for their knowledge. Rather than simply acknowledging courtroom expectations by deliberating based on only the facts presented in the courtroom, jurors are asking for more evidence than that is provided or necessary because jurors are comparing forensic evidence used to convict on television to real life cases. Thus, jurors are not impartial to the case because they have a prenotion of what information they require to convict, such as fingerprints in burglaries and blood analysis in murder cases. Smith et all reports that viewers of CSI-type shows and other similar shows have “inflated perceptions of accuracy, reliability, and usefulness of forensic evidence (but not ‘nonscientific’ evidence)” (qtd. in Stinson et all). As CSI-type shows emphasize the collection, analysis, and presentation of forensic evidence during court proceedings more so than other types of
A judge has the ability to choose to alter their decision for sentencing based on their respective state’s truth in sentencing program. Depending on the crime and the offender, a judge may decide to mandate the offender to a longer than average sentence. The judge may change the offender’s base sentence. It may be reduced to match a sentence that is similar to a non-truth in sentencing punishment. He or she knows the offender will only serve about eighty-five percent of the sentence before they are eligible for parole or released. By minimizing the sentence, the eighty-five percent served would resemble a sentence that allowed for early release (Chen, 2001, page ii). However, the judge may form a bias of the individual and use this power to order them to a greater amount of time in order to punish the person. An individual who commits a crime, especially a violent crime, would serve almost double the average sentence served (Ditton and Wilson, 1999, pages 7-8). It would also force individuals, who commit less severe crimes to serve longer sentences since they are serving the majority of their sentence. A bias of the offender, which can be based on any extralegal factor, may lead to an injustice sentence and truth in sentencing would not allow them to be released early. There are also innocent people within the criminal justice system that may be falsely convicted.
- The second method I will use is calculating probabilities by the use of conditional probability.
... up with a verdict for the accused person (Lamb, 2013). This is because the jury is filled with laymen who do not have any understanding of the law, and if they are allowed to deliberate on the evidence produced in court, then they may be misguided and may at many times find the accused person innocent while in the real sense they were guilty.
Probability is always surrounding us from stock markets to the ever-simple heads or tails. This very complicated area of mathematics can be explained in a simpler way. It is how likely an event is to happen. The probability of an event will always be between 0 and 1. The closer it is to one, the more likely the event is to happen.
...entity beyond a reasonable doubt, then neither could a second test on an even smaller sample.”