Simple Linear Regression and the Correlation Coefficient

Cheng-Few Lee, John C. Lee and Alice C. Lee
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Cheng-Few Lee: Rutgers University Business School, Department of Finance and Economics
John C. Lee: Center for PBBEF Research

Chapter Chapter 13 in Statistics for Business and Financial Economics, 2013, pp 615-674 from Springer

Abstract: 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.

Keywords: Regression Line; Scatter Diagram; Bond Price; Bivariate Normal Distribution; Simple Regression Analysis (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-5897-5_13

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DOI: 10.1007/978-1-4614-5897-5_13

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