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Regression Analysis

Alan M. Rubin


The essence of scientific research is explaining and predicting relationships among variables. Two or more variables co-vary and are related if their values systematically correspond to each other. In other words, as one value increases or decreases, the other value consistently or systematically increases or decreases (→  Correlation Analysis ). For example, researchers might observe the amount of Internet use increases from younger to older adolescence, leading them to expect a relationship between Internet use and age of adolescents. As scientists seek to explain phenomena, they employ various empirical measures to express relationships among two or more variables. Correlation is a measure of such relationships. The Pearson product–moment correlation coefficient assesses the magnitude and direction of a relationship between two linear variables, and describes how proportional the values of the variables are to each other ( StatSoft 2006 ). A multiple correlation coefficient does this for three or more variables, such as age, education level, and amount of Internet use. There are similar tests, such as gamma and phi, for relationships among nonlinear, categorical, or rank-order variables (→  Measurement Theory ). From a correlation coefficient we might conclude there is a positive and significant relationship between amount of Internet use and age of adolescents. A correlation ... log in or subscribe to read full text

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