Calculate the sensitivity (d') for each session and subject. ### Table 1: Areas Under the Standard Normal Curve from 0 to zThis table provides the cumulative probabilities (areas) under the standard normal curve for values ranging from 0 to z. Each entry in the table represents the area under the curve from the mean (0) to the specified z-value.#### Structure of the Table:- **Rows:** Represent different z-values (z) from 0.0 to 3.9, increasing in increments of 0.1.- **Columns:** Represent additional decimal places from 0.00 to 0.09.To find the area for a specific z-value, use the row corresponding to the integer and one decimal place of the z-value, and the column corresponding to the second decimal place.#### Example:If you are looking for the cumulative probability for a z-value of 1.23:1. Go to the row labeled "1.2".2. Move across to the column labeled "0.03".3. The intersection gives the area: 0.8907.This value means that 89.07% of the data lies between the mean and a z-value of 1.23 in the standard normal distribution.Refer to this table to find cumulative probabilities for various z-values quickly. This is especially useful in statistics for calculating the probability of a value occurring within a certain range in a normally distributed dataset. ### Signal Detection Theory Experiment DataThe following data were collected on two subjects during an SDT (Signal Detection Theory) experiment.#### Data Table| Session | Subject 1 (Hit Rate, FA Rate) | Subject 2 (Hit Rate, FA Rate) ||-----------|-------------------------------|-------------------------------|| Session 1 | 0.80, 0.44 | 0.99, 0.63 || Session 2 | 0.65, 0.27 | 0.85, 0.15 || Session 3 | 0.40, 0.10 | 0.50, 0.02 |#### Receiver Operating Characteristics (ROC) CurvesThe ROC curves for each subject are plotted below. The ROC curve is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied. It is created by plotting the True Positive Rate (Sensitivity) against the False Positive Rate (1-Specificity).- **X-axis (P(FA))**: The probability of a False Alarm (False Positive Rate).- **Y-axis (P(Hit))**: The probability of a Hit (True Positive Rate).The dark gray diagonal line represents the line of no discrimination, where the probabilities of hits and false alarms are equal, indicating random guessing.![ROC Curve](ROC_curve.png)(Note: Image of the ROC curve could not be transcribed. Please refer to the visual graph provided.)#### Sensitivity CalculationTo calculate the sensitivity (d') for each session and subject, use the formula:\[ d' = z[Hit rate - .5] + z[.5 - FA rate]\]**Important Note**: Compute the values inside the brackets \(\{\}\) first, then find the z-transform of those values before adding them together.Use the following table to compute d' for each session and subject.##### Calculation Table| Session | Subject 1 d' | Subject 2 d' ||-----------|--------------|--------------|| Session 1 | d' = ______ | d' = ______ || Session 2 | d' = ______ | d' = ______ || Session 3 | d' = ______ | d' = ______ |Fill in the blanks with the appropriate calculated d' values using the provided formula.

In this question, data from a Signal Detection Theory (SDT) experiment is provided for two subjects.…

Table 1 Areas Under the Standard Normal Curve from 0 to z N 0.00 0.01 0.02 0.03 0.0 .0000 .0040 .0080 .0120 0.1 .0398 .0438 .0478 .0517 0.2 .0793 .0832 .0871 .0910 0.3 .1179 .1217 .1255 0.4 .1554 .1591 .1628 .1985 .2019 0.5 .1915 .1950 0.6 .2258 .2291 .2324 .2357 0.7 2580 0.8 2881 .2910 .2939 0.9 .3159 .3186 .3212 1.0 .3413 .3438 .3461 1.1 .3643 .3665 .3686 1.2 .3849 .3869 .3888 1.3 .4032 .4049 .4066 1.4 .4192 .4207 .4222 0.04 0.05 0.06 .2190 .2224 .2054 2088 .2123 2157 .2389 .2422 .2454 .2486 .2518 .2549 .2612 .2642 .2673 .2704 .2734 .2764 .2794 .2823 .2852 .2967 .2996 .3023 .3051 .3078 .3106 .3133 .3238 .3264 .3289 .3315 .3340 .3365 .3389 .0319 .0359 .0160 .0199 .0239 .0279 .0557 .0596 .0636 .0675 .0714 .0754 .0948 .0987 .1026 .1064 .1103 .1293 .1331 .1368 .1406 .1443 .1480 .1700 .1736 .1772 .1808 .1844 .1141 .1517 .1664 .1879 1.5 .4332 .4345 .4357 .4370 1.6 .4452 .4463 .4474 .4484 1.7 .4554 .4564 1.8 .4641 .4649 1.9 .4713 .4719 .4573 .4582 .4656 .4664 .4726 .4732 .3485 .3508 .3708 .3729 .3907 .3925 .4082 .4099 .4236 .4251 .4265 3.0 .4987 .4987 .4987 3.1 .4990 .4991 .4991 3.2 .4993 .4993 .4994 3.3 .4995 .4995 .4995 3.4 .4997 .4997 .4997 0.07 0.08 .3577 .3599 .3531 .3554 .3749 .3770 .3790 .3944 .3962 .3980 .4115 .4131 .4147 .4279 .4292 .4788 .4793 .4798 .4803 .4808 .4834 .4838 .4842 .4846 .4850 2.0 4772 .4778 .4783 2.1 .4821 .4826 .4830 2.2 .4861 .4864 .4868 .4871 .4875 .4878 .4881 .4884 .4887 2.3 .4893 .4896 .4901 .4904 .4906 .4909 .4925 .4927 .4929 .4931 .4898 2.4 4918 .4920 .4922 .4988 .4988 .4991 .4992 .4994 .4994 .4996 .4996 .4997 .4997 .4382 .4394 .4406 .4418 .4429 .4441 .4495 .4545 .4505 .4515 .4525 .4535 .4591 .4599 .4608 .4616 .4625 .4633 .4671 .4678 .4686 .4693 .4699 .4706 .4738 .4744 .4750 .4756 .4761 .4767 2.5 .4938 .4940 .4941 4943 .4945 .4946 2.6 .4953 .4955 .4956 .4957 .4959 .4960 2.7 .4965 .4966 .4967 .4968 .4969 .4970 .4971 .4972 2.8 .4974 .4975 .4976 .4977 .4977 .4978 .4979 2.9 .4981 .4982 .4982 .4983 .4984 .4984 .4985 .3621 .3810 .3830 .3997 .4015 .4162 .4177 .4306 .4319 .4998 .4999 3.5 .4998 .4998 .4998 .4998 .4998 3.6 .4998 .4998 .4999 .4999 .4999 .4999 .4999 .4999 .4999 .4999 .4999 .4999 .4999 .4999 .5000 .5000 .5000 5000 .4999 .4999 .4999 3.7 3.8 3.9 .5000 .5000 0.09 .4989 .4992 .4812 .4817 .4854 .4857 .4890 .4911 .4913 .4916 .4932 .4934 .4936 .4948 .4949 .4951 .4952 .4961 .4962 .4963 .4964 .4973 .4974 .4979 .4980 .4981 .4985 .9486 .4986 .4989 .4989 .4990 .4992 .4992 .4994 .4994 .4995 .4996 .4996 .4997 .4997 .4990 .4993 .4993 .4995 .4995 .4996 .4996 .4997 .4997 .4997 .4998 .4998 .4998 .4999 .4999 .4999 .4999 .4999 .4999 .4999 .5000 .5000 .5000 .4998 .4998 .4999 .4999 .4999 .4999 .4999 .5000