Linear Regression Using R: An Introduction to Data Modeling
by David R. Lilja
Publisher: University of Minnesota 2016
Number of pages: 91
The book presents one of the fundamental data modeling techniques in an informal tutorial style. Learn how to predict system outputs from measured data using a detailed step-by-step process to develop, train, and test reliable regression models. Key modeling and programming concepts are intuitively described using the R programming language.
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by Ivan Lowe - scientificlanguage.com
The book begins by expanding on some of the basic concepts such data types and variables. The basic choice then is between the family of statistics which compares groups, and the family which studies associations or correlations.
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.
by Jonathan A. Poritz - Colorado State University, Pueblo
This is a first draft of a free textbook for a one-semester, undergraduate statistics course. Contents: One-Variable Statistics - Basics; Bi-variate Statistics - Basics; Linear Regression; Probability Theory; Bringing Home the Data; Basic Inferences.
Statistics is the study of the collection, analysis, interpretation, presentation and organization of data. It deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments.