Internal reliability audits show the following historical li…

Internal reliability audits show the following historical likelihoods of a late shipment for each carrier:P(Late | MediShip) = 0.05P(Late | QuickRx) = 0.10P(Late | PharmaFly) = 0.25 Market share (prior probabilities) for shipments:P(MediShip) = 0.40P(QuickRx) = 0.30P(PharmaFly) = 0.30A hospital administrator calls to report a shipment is Late. Given that the shipment is Late, what is the probability it was carried by PharmaFly?

Case Study 1: GlobalMed Surgical Supply Chain You are the Op…

Case Study 1: GlobalMed Surgical Supply Chain You are the Operations Director for “GlobalMed,” a distributor of critical surgical kits to hospitals. In the healthcare industry, on-time delivery is a matter of life and death. You are currently evaluating the performance of your three primary courier services: MediShip, QuickRx, and PharmaFly.   You have compiled a dataset of 500 recent shipments. The data includes the Carrier Name, Region, Promised Delivery Date, and Actual Delivery Date. Your executive team needs a precise statistical breakdown of reliability. Specifically, there is a perception that PharmaFly is frequently late with international shipments, but you need to prove this with probability data before renegotiating contracts. See Spreadsheet:  Midterm_GlobalMed_500_Shipments.csv Data Summary Table: Carrier Total Shipments On-Time Late MediShip 200 190 10 QuickRx 150 135 15 PharmaFly 150 115 35 Total 500 440 60