Here data of Operator 1 and 2 is as
Operator 1 | Signal | |
Present | Absent | |
Yes | 1800 | 1500 |
No | 200 | 500 |
p(Hit)= 1800/3300 = 0.55 | p(FA)= 1-0.55 = 0.45 | |
z(Hit)= z(0.55) = 0.13 | z(FA)= z(0.45) = -0.12 |
Discriminant index = d' = z(Hit) - z(FA) = 0.13 + 0.12 = 0.25
and Criterion Value = Yc = -[z(Hit) + z(FA)] / 2 = -(0.13-0.12)/2 = -0.01/2 = -0.005
Similarly
Operator 2 | Signal | |
Present | Absent | |
Yes | 600 | 60 |
No | 1400 | 1940 |
p(Hit)= 600/660 = 0.91 | p(FA)= 1-0.91 = 0.09 | |
z(Hit)= z(0.91) = 1.34 | z(FA)= z(0.09) = -3.13 |
Discriminant index = d' = z(Hit) - z(FA) = 1.34 + 3.13 = 4.47
and Criterion Value = Yc = -[z(Hit) + z(FA)] / 2 = -(1.34 - 3.13)/2 = 1.79/2 = 0.895
Here based on relationship between Yc and d' we classify the operators as
For operator 1st Yc = -0.005 so Here the observer is said to be ‘unbiassed’ in favour of ‘yes’ responses.
And For operator 2nd Yc = 0.895 so Here the observer is said to be ‘unbiassed’ in favour of ‘No’ responses.
6) Performance data collected during a working day for two operators working on different luggage scanners...
7) Following table represents the performance data of an operator for two signal detection tasks. Calculate the criterion value (Yc) and Discriminability index (d') (12.5 points) Compare the difficulty level the tasks (2.5 points) Task 1 Response Signal Noise Yes Signal 475 30 Yes Noise 25 470 Task 2 Response Signal Noise Yes Signal 305 200 Yes Noise 195 300