Appendix 8.2 The Falsification of Evolution

Now things start to get interesting but let me first examine the coin toss model;  

To guess 7 H-T tosses in a row we note there is 2^7 or 128 ways of arranging 7 coins which actually means this will occur on average every 128 tosses of seven coins for a total of 896 coin tosses and that is the work required to both create the order and pay the entropy cost required by the second law for that state of order in that system and by that process. It is vital you understand the connection with entropy at this point since entropy is a measure of disorder and disorder is the probability of a state of matter existing. That is from Boltzmann's [ s = k.logW ] Disorder = W/Wtot where W is the number of microstates in a chosen macrostate and Wtot is the total number of microstates in the system. In this case W = 1 (one way to get an exact sequence of H-T) out of Wtot = 128 (possible arrangements) and the disorder is the probability of that state = 1/128 = 0.0078 while the entropy is log 1 = 0 as it is the most ordered state you can get from that system. There is something else; we know work is the only form of energy that can create thermodynamic order. Work is also a product of vectors which have direction as well as magnitude implying a choice has to be made. So work is directed energy while heat is random energy and creates only disorder unless directed. 

Note however to get one arrangement of 7 in a row starting with an audience (population) and using selection to cull it only took 7 generations of selection events. Knowing the chance of selection 0.5 we can predict the population required since it is on average halved 7 times from an initial starting population = 2^7 or 128. The total number of coin tosses (mutations) = 128 + 64 + 32 + 16 + 8 + 4 + 2 + 1 = 254 so selection reduced the number of mutations required by (896 - 254)/896 x 100% = 71.6% revealing the power of selection over pure chance. The model tests survival in response to a changing environment. By starting with a population and introducing successive random mutations then selecting survivors matching an external random event and culling the rest it is a model of pure highly optimised selection. All we need now is to give this model the same task that evolution in the wild must have had, i.e. grow a new gene with no target to aim for just a fitness landscape to respond to.