By virtue of completing this course, you are now an informed consumer of researc
ID: 3256570 • Letter: B
Question
By virtue of completing this course, you are now an informed consumer of research. read this blog post. Then discuss the ethical and policy implications of the reported research.
Lying with Statistics: Today's Example CNN: "Report: Fatalities soar after helmet law lifted" "Motorcycle fatalities involving riders without helmets have soared in the nearly six years since Gov. Jeb Bush repealed the state's mandatory helmet law, a newspaper reported Sunday. A Florida Today analysis of federal motorcycle crash statistics found "unhelmeted" deaths in Florida rose from 22 in 1998 and 1999, the years before the helmet law repeal, to 250 in 2004, the most recent year of available data. Total motorcycle deaths in the state have increased 67 percent, from 259 in 2000 to 432 in 2004, according to National Highway Traffic Safety Administration statistics. Records, though, also show motorcycle registrations have increased 87 percent in Florida since Bush signed the helmet law repeal July 1, 2000.” Deaths went up 67%, registrations went up 87%, so deaths per motorcycle have been going down. "Unhelmeted deaths" went up steeply, which sounds convincing—until you realize that one result of not wearing a helmet is that an accident that would have killed you even with a helmet now counts as an "unhelmeted" instead of a "helmeted" death. I do not know what else changed over the period; it would be interesting so see comparable statistics from states that did not change their laws. But the evidence actually presented in the article, taken by itself, implies precisely the opposite of what the top level headline suggests.
Explanation / Answer
Under certain conditions it is possible to manipulate results of some experiments these conditions are usually observed when there is some hidden variable which is left undiscovered it is sometimes left out of the model for the sake of lying which is too dangerous especially in policy making.
The example stated uin the above case is just the later case as we see that with the inclusion of the increase of number of bikes on road makes the correlation exactly the opposite of what is suggested i.e. there is a decline in per person deaths if we include the two variable togather in the model while if keep the total number of bikes left out of the model then the model will tell us that there is actually an increase in the death with more people wearing helmets which doesent make sense.
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