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Gaussian-Based Data Analysis

  • Jeffrey S. Simonoff
Chapter
  • 1.2k Downloads
Part of the Springer Texts in Statistics book series (STS)

Abstract

In the next two chapters we examine univariate and regression analysis based on the central distribution of statistical inference and data analysis, the normal, or Gaussian, distribution. It is important to note that the brief overview of least squares regression given here is not a substitute for the thorough discussion that would appear in a good regression textbook. See the “Background material” section of this chapter for several examples of such books.

Keywords

Maximum Likelihood Estimator Grade Point Average Target Variable Gaussian Random Variable Standard Normal Random Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Jeffrey S. Simonoff
    • 1
  1. 1.Leonard N. Stern School of BusinessNew York UniversityNew YorkUSA

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