Abstract
In Chapter 13, we formulated the problem of linear regression for observation pairs (X,Y) as the problem of fitting a straight line y = a + βx to a scatter diagram representingNsample points (X1Y1),…,(XNYN). Following our usual approach, we defined sets of elementary estimates for the regression parameters a and β. These elementary estimates not only allowed us to find estimates for a and β, but also to determine a test for the independence of the variables X and Y as well as to measure the strength of relationship between X and Y by means of the Kendall correlation coefficient.
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© 1991 Springer Science+Business Media New York
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Noether, G.E. (1991). Least Squares Regression and Correlation. In: Introduction to Statistics. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-0943-0_14
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DOI: https://doi.org/10.1007/978-1-4612-0943-0_14
Publisher Name: Springer, New York, NY
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