Reference no: EM13367534

Question 1. Assignment on Regression, part 3: You are a real estate Agent. A prospective client in Aurora Hills comes and would like to sell his house. He his asking how much he could ask for his house with a lot of 6612 square feet, and 4 bedrooms. The house is 86 hours old.
Based on our houses Regression model, write a business letter to this prospective client to give an estimate of the recommended list price.

Question 2. Assignment on Linear Programming:
2.1     Maximize 3 X₁  +  X₂

     Subject to:
      X₁  ≤  10

      X₂ ≤  10

      X₁  +  X₂  ≤ 15

a.      Outline the feasible region on a graph
b.      Determine the optimal solution

Question 2.2     You need to buy some filing cabinets. You know that Cabinet X costs $10 per unit, requires six square feet of floor space, and holds eight cubic feet of files. Cabinet Y costs $20 per unit, requires eight square feet of floor space, and holds twelve cubic feet of files. You have been given $140 for this purchase, though you don't have to spend that much. The office has room for no more than 72 square feet of cabinets. How many of which model should you buy, in order to maximize storage volume?

Question: 2.3 George Johnson recently inherited a large sum of money; he wants to use a portion of his money to set up a trust fund for his two children. The trust fund has two investment options: (1) a bond fund and (2) a stock fund. The projected returns over the life of the investments are 6% for the bond fund and 10% for the stock fund. Whatever portion of inheritance he finally decides to commit to the trust fund, he wants to invest at least 30% of that amount in the bond fund. In addition, he wants to select a mix that will enable him to obtain a total return of at least 7%.
Formulate a linear programming model that can be used to determine the percentage that should be allocated to each of the possible investment alternatives.

2.3     In a 100 words total, comment on:
a.      The relevance of Linear Programming in Economics, and
b.       the relevance of Linear Programming to the Manager