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Essay / Research Paper Abstract
This 5 page paper gives a brief overview of linear regression, then details the correlation of the regression to independent variables. One graph included. Bibliography lists 3 sources.
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5 pages (~225 words per page)
File: D0_MBstatlin.rtf
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Unformatted sample text from the term paper:
2001). For example, if one knows the relationship between advertising expenditures and sales, then predictably, one can judge sales by regression analysis once the level of advertising budget has been
set. Following a mathematical principal much like subtraction, one can balance the equation going forward or backward to arrive at the missing variable. Correlation is used when you have measured
two variables in each subject, and wish to quantify how consistently the two variables vary together. When the two variables vary together, statisticians say that there is a lot of
covariation or correlation(Montgomery, 2001). The correlation factor, generally represented as Y can be said to be the known factor, that which
is going to be compared. This generally remains constant, but if it changes the changes are known. For example, Y is the known factor such as a test (a drivers
test for instance) and the unknown variable would be the person taking the test and their score on the test, represented by X. Then, one would want to randomly select
people from the DMVs data base who had taken the test and list their scores. This would then end up being the random sample from the variable element of population,
or X (as represented). Thus it can be stated that Simple Linear Regression is the method for finding the "line of best fit" between the dependent variable, y, and the
independent variable, x. There are a number of quantitative terms that one must familiarize oneself with before going much further in statistical analysis. Most analysis may consist of only one
independent variable, and in such cases the analysis or linear characteristic is said to be simple or Simple Linear Regression. The independent variable, or that variable that may fluctuate is
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