Research Paper on:
Sex Survey Statistical Analysis

Unformatted Sample Text from the Research Paper:
example of this would be when a person leaves school and attempts to understand the professional manuals or to do some research for their employer. Consequently, the specific words we  use to communicate results of data analyses can have an impact on others (and our own) understanding of the meaning of statistical tests. Evidence indicates that  many scientists fail to accurately interpret the meaning of common statistical analyses used to test hypotheses. A solution to this problem may very well be in the way inferential statistical  tests are applied in the real world. For example, a recent issue of the Evening Standard reported that Women who live in London and the South-East are the most likely  to be unfaithful to their partners(Smith 2002). Most people will simply say to themselves that it is interesting information and will either forget it, or begin to do something which  is inherently more dangerous: believe it. The math involved here is not difficult. Investing a few seconds of thought will demonstrate how silly these statistics are. Yet because they come  from George Will or Ann Landers or a news story claiming that "statistics say," people will tend to believe it, and then consequently repeat these same numbers that the simplest  analysis show to be untrue. Using linear regression and correlation, one can see that some of the numbers given in Ms. Smiths article cannot possibly be feasible and are  often contradictory. Regression analysis is a statistical tool that utilizes the relation between two or more quantitative variables so that one variable (dependent variable) can be predicted from the others  (independent variables). For example, if one knows the relationship between advertising expenditures and sales, one can predict sales by regression analysis once the level of advertising expenditures has been set.