Election Fraud: Uncertainty, Logic and Probability

http://richardcharnin.wordpress.com/201 ... -of-fraud/

Oct. 29, 2012

Everyone thinks about problems every day. But how sure are they that their conclusions on how to solve them are valid? My new book Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts deals with uncertainty in our election systems. How do we know that the votes are counted as cast? If the information we are given is tainted, how do we know? We must distinguish between intuitive and logical reasoning. Yet decisions must be made everyday where there are multiple choices.

http://www.amazon.com/Matrix-Deceit-For ... ewpoints=1

Which make the most sense? Which is the most probable? If you flip a coin and it comes up heads five times in a row, is the next flip more likely to be tails? Is a baseball player with a .300 batting average who has not had a base hit in his last 10 at bats due to get one his next time up? In decision making, we always need to consider probabilities.

In mathematics we need unambiguous definitions and rules. In other words, we need logical thinking. Logic is defined as a systematic study of the conditions and procedures required to make valid inferences.

We start with a statement and infer other statements are valid and justified as a consequence of the initial statement. It is important to note that logical inference does not mean the statement is true, only that it is valid. If the starting statement is true, then a logically derived result must also be true.

For example, it is a statement of fact that Bush had 50.5 million recorded votes in 2000. Approximately 2.5 million Bush 2000 voters died prior to the 2004 election, so there could not have been more than 48 million returning Bush voters. But according to the 2004 National Exit Poll, there were 52.6 million returning Bush voters. This is clearly impossible.

Furthermore, since the 2004 National Exit Poll was impossible and adjusted to match the recorded vote, then the recorded vote must also have been impossible. This simple deductive reasoning proves 2004 Election Fraud. But the recorded 2000 vote was also fraudulent - as were all elections before that. None reflected true voter intent. The simple proof: there were 6-10 million uncounted votes in every election prior to 2004. Votes cast exceeded votes recorded by 6-10 million. And 70-80% of the uncounted votes were Democratic.

Each National Exit poll is forced to match the bogus recorded vote based on bogus returning voters from the prior bogus election. It's a recursive process. The polls assume all elections are fair and accurate. The same returning voter logic applied to the 1988, 1992 and 2008 elections shows that they were also fraudulent; the National Exit Polls were forced to match the recorded vote by indicating there were more returning Bush voters than were alive to vote. The corporate media has never seen fit to explain these recurring impossibilities.

Science is “cumulative”. New developments may refine or extend past knowledge. There is no such thing as a foolproof system. What is needed is a probability-based system for many types of problems. It is the only rational way of thinking.

There is no way to eliminate all risk (error) in a system model (or election poll). The problem is to evaluate risk and measure it based on a probability analysis. Every important problem requires a comparison of the odds. Probability analysis supplements classical logical thinking but does not replace it. In fact, classical logic is required in every step in the development of probability theory.