R square Coefficient

R square Coefficient - even remain stable based on the past...

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An R square coefficient of determination refers to the proportion of variability in a statistical model or statistical data. The main purpose of an R square coefficient is to help in the prediction of future outcomes on the basis of other relevant and related information which forms the basis of the predictions as they depict certain trend and tendencies. It provides useful information on the variance that exists in the data which helps in analysis of risk. For example, in case of evaluations and analysis of stocks in the stock market the R square coefficient helps predict if the prices of the shares would increase in the future or if the prices will decrease in the future or
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Unformatted text preview: even remain stable based on the past data of a particular stock. In this way R square coefficient will help in the process of analysis and future predictions. Essentially, a correlation exists between two variables when the value of one variable are somehow associated with the values of the other variable. Correlation does not prove causation; causation is a causing or producing an effect. Yet correlation is entirely important if it is a known fact that the variables are related and then an R square coefficient of determination can be used....
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This note was uploaded on 02/05/2012 for the course ACCT 305 taught by Professor Charlie during the Spring '11 term at University of Phoenix.

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