Fall 2016 Computer Science 458 Lecture 12: 10/17/2016
Per piazza posting, Jieung Kim office hours: Monday and
Wednesdays, 5:30 pm to 7:30pm. AKW 311.
Here is a
draft list of sample final projects.
Final projects are due the last day of reading period.
Guest speaker Monday October 24th: Sam Shleifer, Kensho.
Mid Term Exam - Today
- 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:
- Write the values of each of the following R expressions.
- Write the values of each of the following Python expressions.
- Write a Python function that replicates the behavior of the following R function.
- Write an R function that replicates the behavior of the following Python function.
- A description of a Monte Carlo simulation problem. Implement it in
either R or Python.
- A description of a capital budgeting problem. Implement it in
either R or Python.
- (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."
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.]
Cognitive Models of Decision Making: VOTE
A Realistic Model of Rationality (More readable PDF version of above.)