Fall 2016 Computer Science 458 Lecture 12: 10/10/2016

Assignment 2

So you might have the following series of calls within sensitivity:

1. decide(optOH, OptSC)
2. decide(optOHlowcost, OptSClowcost)
3. decide(optOHhighcost, OptSChighcost)
4. decide(optOHlowdiscount, OptSClowdiscount)
5. decide(optOHlowcostpercar, OptSClowcostpercar)
6. usw. (etc.)

This is a first level approach. You could add more sophistication by calculating the correlations among the variations. You could also include the probabilities of each scenario and then calculate an expected value for all possibilities, if that makes sense.

Finally, you need to be prepared to take handle other options, besides the ones specified. For example, you could have two Ohio plant options, one of which is the given one, and another with a lower cost factory that produces fewer cars.

Mid Term Exam

• There will be a mid term exam in class on Monday October 17th.

• The exam will mostly comprise programming questions in R and Python. Any finance questions will be framed as programming questions. For example, here is the formula for computing the beta of a stock portfolio. Implement that in R or Python.

• The scope of the questions will be as follows:
  • R: The R Cookbook, chapters 1 - 9.
  • R: the swirl tutorial.
  • Python: The Python Cookbook, chapters 1 - 8.

• The questions will primarily be short answer, e.g., what output does this code produce? or what code would produce this output?

• You are not allowed to bring books or computers or other electronic devices. However, you are permitted to bring a single sheet of letter sized paper containing notes on Python and or R on both sides. You must handin your sheet along with your exam.

• Below is the basic structure of the exam:
  1. Write the values of each of the following R expressions.
  2. Write the values of each of the following Python expressions.
  3. Write a Python function that replicates the behavior of the following R function.
  4. Write an R function that replicates the behavior of the following Python function.
  5. A description of a Monte Carlo simulation problem. Implement it in either R or Python.
  6. A description of a capital budgeting problem. Implement it in either R or Python.
  7. (Actual question) Write a description of a final project for this course. You should indicate whether this is a project you would like implement, or that it is purely speculative. You should specify the problem domain (e.g., finance, politics, medicine, dating, movies, etc.), the implementation language (e.g., R, Python, etc.), the decision making paradigm (e.g, Monte Carlo, expected value, linear regression, rule based system, case base system, etc.). Describe the behavior of the program, e.g., use cases or "for this input, the program gives this output." You should describe how the system would work. This could be a process model, a flow chart, list of data structures, etc. You are welcome to choose one of the sample final projects. [Note: given that I am telling you this ahead of time, it should be very difficult to lose points.]

Lecture