Residuals and Influence in Regression
by R. Dennis Cook, Sanford Weisberg
Publisher: Chapman & Hall 1982
Number of pages: 240
Residuals are used in many procedures designed to detect various types of disagreement between data and an assumed model. In this monograph, we present a detailed account of the residual based methods that we have found to be most useful, and brief summaries of other selected methods. Our emphasis is on graphical methods rather than on formal testing.
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by Robert B. Ash - University of Illinois
These notes are based on a course that the author gave at UIUC. No prior knowledge of statistics is assumed. A standard first course in probability is a prerequisite, but the first 8 lectures review results that are important in statistics.
by Philip B. Stark - University of California, Berkeley
This text was written for an introductory class in Statistics for students in Business, Economics, or Social Science. This is the first and last class in Statistics. It also covers logic and reasoning at a level suitable for a general course.
by Frederic Barbaresco, Frank Nielsen (eds) - MDPI AG
Contents: Geometric Thermodynamics of Jean-Marie Souriau; Koszul-Vinberg Model of Hessian Information Geometry; Divergence Geometry and Information Geometry; Density of Probability on manifold and metric space; Statistics on Paths and Manifolds; etc.
by Peter Young - arXiv
These notes discuss, in a style intended for physicists, how to average data and fit it to some functional form. I try to make clear what is being calculated, what assumptions are being made, and to give a derivation of results.