A network representation of a transportation problem has 2 s…

A network representation of a transportation problem has 2 supply nodes and 3 demand nodes connected by 6 distribution routes. The owner of the logistics company wants to minimize costs to meet the demand. Each origin and destination is represented by a node, and each shipping route by a directed arc indicating the flow of goods from supply to demand locations. In this Ohio-based scenario, the origin nodes are Columbus and Cleveland. The destination nodes are Cincinnati, Toledo, and Dayton. The Columbus node is the starting point of three arrows directed toward Cincinnati, Toledo, and Dayton, with transportation costs per unit of $12, $9, and $8, respectively. The Cleveland node is also the starting point of three arrows directed toward Cincinnati, Toledo, and Dayton, with transportation costs per unit of $10, $6, and $7, respectively. Here is the spreadsheet again in the 4th tab: BANA_II_2026_Spring_Final_Exam-2-3.xlsx Supply Nodes (Origins): Columbus (Supply: 40 units) Cleveland (Supply: 30 units) Demand Nodes (Destinations): Cincinnati (Demand: 25 units) Toledo (Demand: 20 units) Dayton (Demand: 25 units)   Transportation Routes (Arcs with Costs) From Columbus: → Cincinnati ($12) → Toledo ($9) → Dayton ($8) From Cleveland: → Cincinnati ($10) → Toledo ($6) → Dayton ($7)

Christina, who is your boss, is looking to buy a car.  The f…

Christina, who is your boss, is looking to buy a car.  The following data is a list of potential cars available to Christina.  She wants to know which factors are statistically significant in predicting miles per gallon for each of the cars she might select.  Develop a multiple regression model that identifies these factors. Provide the model equation and outputs. Explain to Christian in simple terms what the model is telling him (explain the p-values). Show your work and give her the best recommendation for the car that optimizes mpg. Data is on the third tab of this spreadsheet: BANA_II_2026_Spring_Final_Exam-2-4.xlsx