Topics: Regression analysis, Linear regression, Errors and residuals in statistics Pages: 2 (589 words) Published: June 10, 2013
SMMD: Term I 2013 Homework Assignment 5 (Due: Saturday, May 25th, 5.00 p.m.)

Instructions 1. This is an individual assignment and will account for 3% of the course grade. 2. It requires the dataset which is available on the course website alongside this homework. Please note that you may not need all of the data available in the file. 3. Please perform the required data analysis using JMP and turn in a brief report of no more than 3 pages (sides). No separate JMP files or appendices should be provided. Please copy and paste any relevant JMP output into the document itself. 4. Please remember to include your name, section number and ID at the top of the assignment. 5. The homework submissions will not be graded for correctness, but rather for effort. The scoring will be binary – you will get full credit if your effort is deemed satisfactory, otherwise you will get no credit. No credit will be given for late submissions. A timely submission that responds to all questions and shows your thinking will be considered satisfactory whether or not your solution is correct. 6. Honor code category 1 applies. This implies that you can refer to any resource within and outside of the course material only with appropriate citations. You can also discuss with other students but the submitted write-up should be entirely your own work. Significant overlaps with other submissions maybe considered as possible instances of violation of the honor code. 7. The solution for the homework assignment will be made available to you after the due date. 8. Have fun. 

The given data tracks the monthly performance of the Apple Computer stock since its inception in 1980 through the end of 2005. The data include 300 monthly returns on Apple, the returns on IBM, as well as returns on the entire stock market, Treasury Bills (short-term, 30-day loans to the government), and inflation. The column Market Return is the return on a value-weighted portfolio that purchases stock in...
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