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Analytic Assessment of the 1992 and 2000 Presidential Electi

            Analytic Assessment of the 1992 and 2000 Presidential Elections.
            
             With respect to what generally determines whether a presidential candidate wins or loses. A certain number of variables can be studied using statistical analysis to receive that information. Those who understand why statistics are important stand a better chance at hypothesizing which candidate will win or lose without a biased qualitative reason behind it. Therefore it is essential if one wishes to make a good hypothesis on who could win that they correctly understand what is important in an election.
             The factors that determine a presidential election are mainly made up of accepted relevant topics. Furthermore they bring to light actual data that can be examined and compared as in the differences between the 1992 and 2000 elections. The main focal point of this document will be to examine the relevance of party identification, approval ratings, the economy, and race. By examining these data sets the contingency will be to point out mainly the obvious of what was found. After which an explanation will be formulated on as to how these factors possibly decide the outcome of an election.
             By using the 1992 and 2000 elections respectively, the plan is to see how these two elections serve as good indicators of the positives and negatives of using data that is accurate yet containing a margin of error. It will be helpful to note that the 2000 election was very close so the data will more than likely reflect a false positive than what actually happened. However, it is science's goal to provide data that is as accurate as possible. So that in turn a rational theory can be formulated from this to expect what the outcome of any given situation will be given its probability.
             Methodology:.
             The data that was used to create this document came from the esteemed University of Michigan's Survey Research Center using the SPSS (Statistical Program for the Social Sciences).


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