Abstract
In Sect. 6.9, we used correlation to provide a measure of the strength of any linear relationship between a pair of random variables X and Y. The random variables are treated perfectly symmetrically; that is, “the correlation between X and Y” is equivalent to “the correlation between Y and X.” In this chapter, we first discuss the linear relationship between a pair of variables without perfect symmetry. In other words, we assume that Y is a dependent variable and X an independent variable: Y depends on X. Then we discuss the bivariate normal relationship and concepts related to the correlation coefficient.
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CITATION STYLE
Lee, C.-F., Lee, J. C., & Lee, A. C. (2013). Simple Linear Regression and the Correlation Coefficient. In Statistics for Business and Financial Economics (pp. 615–674). Springer New York. https://doi.org/10.1007/978-1-4614-5897-5_13
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