Type I errors: Unfortunately, neither the legal system or statistical testing are perfect. A jury sometimes makes an error and an innocent person goes to jail. Statisticians, being highly imaginative, call this a type I error. Civilians call it a travesty. In the justice system, failure to reject the presumption of innocence gives the defendant a not guilty verdict. This means only that the standard for rejecting innocence was not met. It does not mean the person really is innocent. It would take an endless amount of evidence to actually prove the null hypothesis of innocence.

Type II errors: Sometimes, guilty people are set free. Statisticians have given this error the highly imaginative name, Type II error.Americans find type II errors disturbing but not as horrifying as Type I errors. A type I error means that not only has an innocent person been sent to jail but the truly guilty person has gone free. In a sense, a type I error in a trial is twice as bad as a type II error. Needless to say, the American justice system puts a lot of emphasis on avoiding Type I errors. This emphasis on avoiding Type I errors, however, is not true in all cases where statistical hypothesis testing is done.

QUESTION 1

Part A) What would be your ideal situation if you are the defendant?

The decision of not rejecting the null hypothesis when the null hypothesis is true. In this scenario the jury would have made the correct decision and found me innocent of a crime that I did not commit. True or False? Explain your reasoning Sin depth.

Part B) What would be your ideal situation if you are the prosecuting attorney?

The alternative hypothesis because the null hypothesis is false and through the power of the test, I was able to gather enough evidence to put the guilty party away. True or False? Explain your reasoning in-depth.