hW1.PNG Dr. Osterholm, who directs the center, explained that accurate testing requires the use of tests that are least likely to result in either false-negative or false-positive results. He characterized some of the drive-in tests that people now seek as \"terrible,\" generating lots of false-negative and false-positive results, in part because of how samples are collected. There are two critical hallmarks of a reliable test that can detect true-positive and true-negative results: sensitivity and specificity. Sensitivity refers to \"how well it correctly identifies those who have the virus infection or antibodies,\" the center's document explains. \"A test with low sensitivity will produce more false-negative results compared with a test that has higher sensitivity.\" Specificity of a test refers to \"how well it correctly identifies those who do not have\" a Covid-19 infection or antibodies to it. Early in the pandemic in this country, the test endorsed by the White House was insufficiently sensitive and specific, potentially missing a significant number of infections, the Food and Drug Administratio reported mid-May. hW1.1.PNG You might think any test with 95 percent sensitivity and 95 percent specificity would be highly accurate. But while these would be great grades on an organic chemistry final, the ability of such a test to render a reliable result is extremely poor: 50 percent of the positive results would not be true positives, Dr. Osterholm said. (You'll have to take my word for this explaining the statistics would require half a column!) \"I can't recommend testing willy-nilly,\" he said. \"We have we smart about it.\" 3) Refer to the NYTimes article "The case for smarter coronovirus testing\" and, in particular to the part of it that starts with "Dr Osterholm, who directs the center, explained that accurate...\" and ends with \"(You will have to take my word for this...)\". (You are welcome to read the entire article but don't have to; reading just the snippet mentioned above will suffice in terms of answering the next questions) The snippet states that any test with 95% sensitivity and 95% specificity would be highly accurate but that, in reality, such a test lacks the ability to render a reliable result and that 50% of the positive results would not be true positives\" i) Express the 50% value as a probability statement ii) The article states that how this 50% value is arrived at can be explained by half a column of statistics. Based on the information given in that paragraph (i.e. the two values of sensitivity and specificity), is it possible to obtain this 50% number? (In other words, is the article correct in this 50% claim that it makes?)