Midterm Project

Midterm Project (deadline: April 30)

1. Predicting prices for industrial products using Microsoft Excel;
a) Explain a product in a very detailed way (provide photos, detailed parameters etc.), as well as its competitors on the market; 
b) Data should be real (minimum 24 periods of time) and corresponding hyperlink should be provided;
c) Please, cosider linear, exponential, logarithmic, polynomial (order 2 and 3), and power regression types;
d) Compare the results (R2, standart deviation);
e) Your report including detailed description, all equations and pictures should be done in Microsoft Office (*.rtf file format) or MikTeX (*.tex file), printed and submitted to me until the deadline mentioned above.

Additional points will be given if:
a) You want to achieve a color harmony in your charts using different color schemes. Please use the links below: 
http://hex.colorrrs.com/ (convertion from HEX to RGB model)
b) You try to predict prices using other regression models which we have not studied (trigonometric etc.)

2. Evaluating and comparing the overal quality of 2 products by taking into account different factors. 
a) Explain 2 products in a very detailed way (provide photos, detailed parameters etc.), as well as its competitors on the market; 
b) Define 7-12 factors for analyzing their quality;
c) Use logical evaluation scale (explain it);
d) Construct radar charts for both products, and some other charts which are necessary for your comparative analysis.
e) Your report including detailed description, all equations and pictures should be done in Microsoft Office (*.rtf file format) or MikTeX (*.tex file), printed and submitted to me until the deadline mentioned above.

Additional points will be given if:
a) You want to achieve a color harmony in your charts using different color schemes. Please use the links below: 
http://hex.colorrrs.com/ (convertion from HEX to RGB model)

Recommended literature:
  • Rudolf J. Freund, William J. Wilson, Ping Sa. (2006). Regression Analysis. Statistical Modeling of a Responce Variable, Elsevier [PDF].