Project I: Compressing Coin Flips

Part I: Binomial data with known bias

Describe the ideas/observations/principles underlying the compressor algorithm, the compression results with the given data sets (rate vs. bias, etc). You can (but do not have to) use also charts, GNU-plot figures etc. to clarify the numerical information.

Part II: Binomial data with unknown bias

What happens when you use the compressor algorithm of Part I with a wrong bias parameter? Describe the ideas/observations/principles underlying the compressor algorithm for unknown binomial data, the compression results the given data sets (rate vs. bias, etc). You can (but do not have to) use also charts, GNU-plot figures etc. to clarify the numerical information.

Note: In both parts you have to implement both compressor and decompressor programs. The programs must compile in Linux. Describe also a simple test case that is testable using your step-by-step instructions. (See also the README file in this directory.)