6. Individual Problems 1.7-6 The HR department is trying to ll a vacant position For a job with a small talent pool. Valid applications arrive every week or so, and the applicants all seem to hrirlg dierent levels of expertise. For each applicant, the HR manager gathers information try trying to verify various claims on the candidate's rum, but some douht about "t'r always lingers when a decision to hire or not is to he made. Suppose that hiring an employee who is a bad t for the oompany results in an error oost of $TOCI, but failing to hire a good employee FELIll'E in an error cost of $501] to the company. Although it is impossible to tell in advanoe whether an employee is a good fit. assume that the probability that an applicant is a T'good fit\" is ISLE. while the probability that an applicant is a \"had fit" is 10.3 = 0.2. Hiring an applicant who is a good t. as Imlell as not hiring an applicant who is a bad t. results in no error costto the company. For each decision in the r'owing table, calculate am]r enter the expected error cost oFH'JaI decision. Reality Goo-It Flt Bad Flt Decision p=lJ.8 p=D.2 E'qulected Error Cost Hire Cost: I] Cost: $700 Do Not Hire Cost: $500 Cost: 0 Suppose an otherwise qualied applicant applis For a job. In order to minimize expected error msts, the HR department should 7 the applicant