Discuss and evaluate the use of statistics in current and historical cases of forensic significance
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The science of statistics refers to two distinct areas of knowledge. One area refers to the analysis of uncertainty and the other area refers to the listing of events, counts of entities for various economic, social, and scientific purposes. It is for these reasons that statistics can be of great value within the area of forensic science. Evidence that is used within a legal setting, contains doubt, which means that this evidence requires some statistical and problematic reasoning which plays an imperative role in the criminal investigation, prosecution and trial. Statistical and problematic reasoning also plays a major part in relation to forensic scientific evidence, such as DNA, which is produced by an expert witness.
In criminal cases, it is important that everyone is able to understand and deal with probability and statistics correctly. Throughout history, many criminal cases have been plagued by misunderstandings relating to statistical information and probabilities that contribute towards incorrect judgements and convictions.
Lucia de Berk Case:
In 2004, a Dutch case surrounding Lucia de Berk, was based on statistical evidence. This particular case showed the risks that occurred when statistical evidence invited problematic “coincidence” reasoning. Lucia de Berk was a paediatric nurse that was found guilty of seven murders and three attempted murders. Her victims were children in her care at the Juliana Children’s Hospital in The Hague. The court was told by that more children had died on her shifts, under her care, that was possible by chance. Dr Henk Elffers told the court that the odds of her presence being a coincidence was approximately one in 340 million. Such a large figure was extremely potent and i...
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... between 18 and 60 in the local area in which the rape had occurred.
• If the chance that the crime was committed by a local man was 75%, it makes the odds at 200,000 to 1.
• There is a 1.8million chance that the accused is guilty.
• There is a one in 3.6 million to one chance that the accused is guilty based solely on other evidence, not the DNA evidence.
• There is a one in two chance that the guilty person will give alibi evidence
• Assuming the chance that the accused is not guilty on DNA evidence is one in 200,000,000.
• 200,000,000 should be divided by 3,600,000, giving a result that the chances that the accused is guilty of 55 to one.
It was determined that the jury wasn’t aware of the more logical and common sense ways in which they could have evaluated the DNA evidence. The jury wasn’t correctly made aware of the meanings or implications on Bayes Theorem.