1. Two way tables to illustrate test results Doctors and scientists often use diagnostic testing to determine the existence of a condition or disease. Positive and false-positive results The results of a test are said to be positive if the feature being investigated is found. Eg people tested positive to diabetes. The results are negative if the feature is not found. However, such tests are not 100% accurarte, so there is always a small chance that a diagnosis is incorrect. When the word false is included (eg false-positive or false-negative) it means the test result was incorrect.

2. Test Result PositiveNegativeTotals Condition PresentTrue positive: condition present and detected False negative: disease present but not detected Condition AbsentFalse positive: disease not present and wrongly detected True negative: disease not present and test indicates this correctly Totals

3. Example 1 The police investigated a bank after money went missing. The police used a lie detector in their interviews. After the guilty person was caught the results were displayed in the table below. PositiveNegativeTotals Employees who lied213 Employees who did not lie72532 Totals926 The tests correctly identified 2 employees who lied The test said that 1 employee who lied was not lying. False-negative 3 employees lied 32 employees did not lie The test correctly showed that 25 employees were not lying The test said that 26 employees were not lying. The test said that 9 employees lied. The test wrongly labelled 7 employees who did not lie as lying. False-positive a)How many employees were tested? b)For how many employees was the lie detector accurate? c)What percentage of the tests were false positives? 35 2 + 25 = 27 7 / 35 × 100 =20%

4. a)Fill in the totals. b)How many of the women tested were pregnant? c)How many women who were not pregnant did the test indicate were pregnant? d)What percentage of the test results were accurate? e)What percentage of the identified as “not pregnant” were pregnant? f)What is the probability that a women selected at random from the group which the test said were “pregnant” was in fact not pregnant? Example 2 Dr Kelly is assessing a new type of pregnancy test. The results are: AccurateNot accurateTotals Pregnant155 Not pregnant260 Totals 20 26 46 41 20 41 / 46 ×100=89·1% 5 0 5 / 31 ×100=16.1%Test said 5 + 26 were “not pregnant” 0 / 15 =0%

5. Today’s work Exercise 6-10 Sheet All questions